Cloud native software-defined network architecture

ABSTRACT

In an example, a method includes processing, by an application programming interface (API) server implemented by a configuration node of a network controller for a software-defined networking (SDN) architecture system, requests for operations on native resources of a container orchestration system; processing, by a custom API server implemented by the configuration node, requests for operations on custom resources for SDN architecture configuration, wherein each of the custom resources for SDN architecture configuration corresponds to a type of configuration object in the SDN architecture system; detecting, by a control node of the network controller, an event on an instance of a first custom resource of the custom resources; and by the control node, in response to detecting the event on the instance of the first custom resource, obtaining configuration data for the instance of the first custom resource and configuring a corresponding instance of a configuration object in the SDN architecture.

This application claims the benefit of India provisional application202141044924, filed Oct. 4, 2021, which is incorporated by referenceherein in its entirety.

TECHNICAL FIELD

The disclosure relates to virtualized computing infrastructure and, morespecifically, to cloud native networking.

BACKGROUND

In a typical cloud data center environment, there is a large collectionof interconnected servers that provide computing and/or storage capacityto run various applications. For example, a data center may comprise afacility that hosts applications and services for subscribers, i.e.,customers of data center. The data center may, for example, host all ofthe infrastructure equipment, such as networking and storage systems,redundant power supplies, and environmental controls. In a typical datacenter, clusters of storage systems and application servers areinterconnected via high-speed switch fabric provided by one or moretiers of physical network switches and routers. More sophisticated datacenters provide infrastructure spread throughout the world withsubscriber support equipment located in various physical hostingfacilities.

Virtualized data centers are becoming a core foundation of the modeminformation technology (IT) infrastructure. In particular, modern datacenters have extensively utilized virtualized environments in whichvirtual hosts, also referred to herein as virtual execution elements,such as virtual machines or containers, are deployed and executed on anunderlying compute platform of physical computing devices.

Virtualization within a data center or any environment that includes oneor more servers can provide several advantages. One advantage is thatvirtualization can provide significant improvements to efficiency. Asthe underlying physical computing devices (i.e., servers) have becomeincreasingly powerful with the advent of multicore microprocessorarchitectures with a large number of cores per physical CPU,virtualization becomes easier and more efficient. A second advantage isthat virtualization provides significant control over the computinginfrastructure. As physical computing resources become fungibleresources, such as in a cloud-based computing environment, provisioningand management of the computing infrastructure becomes easier. Thus,enterprise IT staff often prefer virtualized compute clusters in datacenters for their management advantages in addition to the efficiencyand increased return on investment (ROI) that virtualization provides.

Containerization is a virtualization scheme based on operationsystem-level virtualization. Containers are light-weight and portableexecution elements for applications that are isolated from one anotherand from the host. Because containers are not tightly-coupled to thehost hardware computing environment, an application can be tied to acontainer image and executed as a single light-weight package on anyhost or virtual host that supports the underlying containerarchitecture. As such, containers address the problem of how to makesoftware work in different computing environments. Containers offer thepromise of running consistently from one computing environment toanother, virtual or physical.

With containers’ inherently lightweight nature, a single host can oftensupport many more container instances than traditional virtual machines(VMs). Often short-lived, containers can be created and moved moreefficiently than VMs, and they can also be managed as groups oflogically-related elements (sometimes referred to as “pods” for someorchestration platforms, e.g., Kubernetes). These containercharacteristics impact the requirements for container networkingsolutions: the network should be agile and scalable. VMs, containers,and bare metal servers may need to coexist in the same computingenvironment, with communication enabled among the diverse deployments ofapplications. The container network should also be agnostic to work withthe multiple types of orchestration platforms that are used to deploycontainerized applications.

A computing infrastructure that manages deployment and infrastructurefor application execution may involve two main roles: (1)orchestration—for automating deployment, scaling, and operations ofapplications across clusters of hosts and providing computinginfrastructure, which may include container-centric computinginfrastructure; and (2) network management—for creating virtual networksin the network infrastructure to enable packetized communication amongapplications running on virtual execution environments, such ascontainers or VMs, as well as among applications running on legacy(e.g., physical) environments. Software-defined networking contributesto network management.

SUMMARY

In general, techniques are described for a cloud-native SDNarchitecture. In some examples, the SDN architecture may include dataplane elements implemented in compute nodes, and network devices such asrouters or switches, and the SDN architecture may also include a networkcontroller for creating and managing virtual networks. The SDNarchitecture configuration and control planes are designed as scale-outcloud-native software with a container-based microservices architecturethat supports in-service upgrades. The configuration nodes for theconfiguration plane may be implemented to expose custom resources. Thesecustom resources for SDN architecture configuration may includeconfiguration elements conventionally exposed by a network controller,but the configuration elements may be consolidated along with Kubernetesnative / built-in resources to support a unified intent model, exposedby an aggregated API layer, that is realized by Kubernetes controllersand by custom resource controller(s) that work to reconcile the actualstate of the SDN architecture with the intended state.

The techniques may provide one or more technical advantages. Forexample, a cloud-native SDN architecture may address limitations inconventional SDN architectures relating to complexity in life cyclemanagement, mandatory high resource analytics components, scalelimitations in configuration management, and the lack of command-lineinterface (CLI)-based interfaces. For example, the network controllerfor the SDN architecture is a cloud-native, lightweight distributedapplication with a simplified installation footprint. This alsofacilitates easier and modular upgrade of the various componentmicroservices for configuration node(s) and control node(s) for theconfiguration and control planes. The techniques may further enableoptional cloud-native monitoring (telemetry) and user interfaces, ahigh-performance data plane for containers using a DPDK-based virtualrouter connecting to DPDK-enabled pods, and cloud-native configurationmanagement that in some cases leverages a configuration framework forexisting orchestration platforms, such as Kubernetes or Openstack. As acloud-native architecture, the network controller is scalable andelastic to address and support multiple clusters. The network controllermay in some cases may also support scalability and performancerequirements for key performance indicators (KPIs).

In an example, a network controller for a software-defined networking(SDN) architecture system, the network controller comprising: processingcircuitry; a configuration node configured for execution by theprocessing circuitry; and a control node configured for execution by theprocessing circuitry, wherein the configuration node includes anapplication programming interface (API) server to process requests foroperations on native resources of a container orchestration system andincludes a custom API server to process requests for operations oncustom resources for SDN architecture configuration, wherein each of thecustom resources for SDN architecture configuration corresponds to atype of configuration object in the SDN architecture system, and whereinthe control node is configured to, in response to detecting an event onan instance of a first custom resource of the custom resources, obtainconfiguration data for the instance of the first custom resource andconfigure a corresponding instance of a configuration object in the SDNarchitecture.

In an example, a method includes processing, by an applicationprogramming interface (API) server implemented by a configuration nodeof a network controller for a software-defined networking (SDN)architecture system, requests for operations on native resources of acontainer orchestration system; processing, by a custom API serverimplemented by the configuration node, requests for operations on customresources for SDN architecture configuration, wherein each of the customresources for SDN architecture configuration corresponds to a type ofconfiguration object in the SDN architecture system; detecting, by acontrol node of the network controller, an event on an instance of afirst custom resource of the custom resources; and by the control node,in response to detecting the event on the instance of the first customresource, obtaining configuration data for the instance of the firstcustom resource and configuring a corresponding instance of aconfiguration object in the SDN architecture.

In an example, a non-transitory computer-readable medium comprisesinstructions for causing processing circuitry to: process, by anapplication programming interface (API) server implemented by aconfiguration node of a network controller for a software-definednetworking (SDN) architecture system, requests for operations on nativeresources of a container orchestration system; process, by a custom APIserver implemented by the configuration node, requests for operations oncustom resources for SDN architecture configuration, wherein each of thecustom resources for SDN architecture configuration corresponds to atype of configuration object in the SDN architecture system; detect, bya control node of the network controller, an event on an instance of afirst custom resource of the custom resources; and by the control node,in response to detecting the event on the instance of the first customresource, obtain configuration data for the instance of the first customresource and configure a corresponding instance of a configurationobject in the SDN architecture.

The details of one or more examples of this disclosure are set forth inthe accompanying drawings and the description below. Other features,objects, and advantages will be apparent from the description anddrawings, and from the claims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram illustrating an example computinginfrastructure in which examples of the techniques described herein maybe implemented.

FIG. 2 is a block diagram illustrating an example of a cloud-native SDNarchitecture for cloud native networking, in accordance with techniquesof this disclosure.

FIG. 3 is a block diagram illustrating another view of components of SDNarchitecture 200 and in further detail, in accordance with techniques ofthis disclosure.

FIG. 4 is a block diagram illustrating example components of an SDNarchitecture, in accordance with techniques of this disclosure.

FIG. 5 is a block diagram of an example computing device, according totechniques described in this disclosure.

FIG. 6 is a block diagram of an example computing device operating as acompute node for one or more clusters for an SDN architecture system, inaccordance with techniques of this disclosure.

FIG. 7A is a block diagram illustrating control / routing planes forunderlay network and overlay network configuration using an SDNarchitecture, according to techniques of this disclosure.

FIG. 7B is a block diagram illustrating a configured virtual network toconnect pods using a tunnel configured in the underlay network,according to techniques of this disclosure.

FIG. 8 is a block diagram illustrating an example of a custom controllerfor custom resource(s) for SDN architecture configuration, according totechniques of this disclosure.

FIG. 9 is a block diagram illustrating an example flow of creation,watch, and reconciliation among custom resource types that havedependencies on different custom resource types.

FIG. 10 is a flowchart illustrating an example mode of operations for anetwork controller of a software-defined networking architecture system,according to techniques of this disclosure.

Like reference characters denote like elements throughout thedescription and figures.

DETAILED DESCRIPTION

FIG. 1 is a block diagram illustrating an example computinginfrastructure 8 in which examples of the techniques described hereinmay be implemented. Current implementations of software-definednetworking (SDN) architectures for virtual networks present challengesfor cloud-native adoption due to, e.g., complexity in life cyclemanagement, a mandatory high resource analytics component, scalelimitations in configuration modules, and no command-line interface(CLI)-based (kubectl-like) interface. Computing infrastructure 8includes a cloud-native SDN architecture system, described herein, thataddresses these challenges and modernizes for the telco cloud-nativeera. Example use cases for the cloud-native SDN architecture include 5Gmobile networks as well as cloud and enterprise cloud-native use cases.An SDN architecture may include data plane elements implemented incompute nodes (e.g., servers 12) and network devices such as routers orswitches, and the SDN architecture may also include an SDN controller(e.g., network controller 24) for creating and managing virtualnetworks. The SDN architecture configuration and control planes aredesigned as scale-out cloud-native software with a container-basedmicroservices architecture that supports in-service upgrades.

As a result, the SDN architecture components are microservices and, incontrast to existing network controllers, the SDN architecture assumes abase container orchestration platform to manage the lifecycle of SDNarchitecture components. A container orchestration platform is used tobring up SDN architecture components; the SDN architecture uses cloudnative monitoring tools that can integrate with customer provided cloudnative options; the SDN architecture provides a declarative way ofresources using aggregation APIs for SDN architecture objects (i.e.,custom resources). The SDN architecture upgrade may follow cloud nativepatterns, and the SDN architecture may leverage Kubernetes constructssuch as Multus, Authentication & Authorization, Cluster API,KubeFederation, KubeVirt, and Kata containers. The SDN architecture maysupport data plane development kit (DPDK) pods, and the SDN architecturecan extend to support Kubernetes with virtual network policies andglobal security policies.

For service providers and enterprises, the SDN architecture automatesnetwork resource provisioning and orchestration to dynamically createhighly scalable virtual networks and to chain virtualized networkfunctions (VNFs) and physical network functions (PNFs) to formdifferentiated service chains on demand. The SDN architecture may beintegrated with orchestration platforms (e.g., orchestrator 23) such asKubernetes, OpenShift, Mesos, OpenStack, VMware vSphere, and withservice provider operations support systems/business support systems(OSS/BSS).

In general, one or more data center(s) 10 provide an operatingenvironment for applications and services for customer sites 11(illustrated as “customers 11”) having one or more customer networkscoupled to the data center by service provider network 7. Each of datacenter(s) 10 may, for example, host infrastructure equipment, such asnetworking and storage systems, redundant power supplies, andenvironmental controls. Service provider network 7 is coupled to publicnetwork 15, which may represent one or more networks administered byother providers, and may thus form part of a large-scale public networkinfrastructure, e.g., the Internet. Public network 15 may represent, forinstance, a local area network (LAN), a wide area network (WAN), theInternet, a virtual LAN (VLAN), an enterprise LAN, a layer 3 virtualprivate network (VPN), an Internet Protocol (IP) intranet operated bythe service provider that operates service provider network 7, anenterprise IP network, or some combination thereof.

Although customer sites 11 and public network 15 are illustrated anddescribed primarily as edge networks of service provider network 7, insome examples, one or more of customer sites 11 and public network 15may be tenant networks within any of data center(s) 10. For example,data center(s) 10 may host multiple tenants (customers) each associatedwith one or more virtual private networks (VPNs), each of which mayimplement one of customer sites 11.

Service provider network 7 offers packet-based connectivity to attachedcustomer sites 11, data center(s) 10, and public network 15. Serviceprovider network 7 may represent a network that is owned and operated bya service provider to interconnect a plurality of networks. Serviceprovider network 7 may implement Multi-Protocol Label Switching (MPLS)forwarding and in such instances may be referred to as an MPLS networkor MPLS backbone. In some instances, service provider network 7represents a plurality of interconnected autonomous systems, such as theInternet, that offers services from one or more service providers.

In some examples, each of data center(s) 10 may represent one of manygeographically distributed network data centers, which may be connectedto one another via service provider network 7, dedicated network links,dark fiber, or other connections. As illustrated in the example of FIG.1 , data center(s) 10 may include facilities that provide networkservices for customers. A customer of the service provider may be acollective entity such as enterprises and governments or individuals.For example, a network data center may host web services for severalenterprises and end users. Other exemplary services may include datastorage, virtual private networks, traffic engineering, file service,data mining, scientific- or super- computing, and so on. Althoughillustrated as a separate edge network of service provider network 7,elements of data center(s) 10 such as one or more physical networkfunctions (PNFs) or virtualized network functions (VNFs) may be includedwithin the service provider network 7 core.

In this example, data center(s) 10 includes storage and/or computeservers (or “nodes”) interconnected via switch fabric 14 provided by oneor more tiers of physical network switches and routers, with servers12A-12X (herein, “servers 12”) depicted as coupled to top-of-rackswitches 16A-16N. Servers 12 are computing devices and may also bereferred to herein as “compute nodes,” “hosts,” or “host devices.”Although only server 12A coupled to TOR switch 16A is shown in detail inFIG. 1 , data center 10 may include many additional servers coupled toother TOR switches 16 of the data center 10.

Switch fabric 14 in the illustrated example includes interconnectedtop-of-rack (TOR) (or other “leaf”) switches 16A-16N (collectively, “TORswitches 16”) coupled to a distribution layer of chassis (or “spine” or“core”) switches 18A-18M (collectively, “chassis switches 18”). Althoughnot shown, data center 10 may also include, for example, one or morenon-edge switches, routers, hubs, gateways, security devices such asfirewalls, intrusion detection, and/or intrusion prevention devices,servers, computer terminals, laptops, printers, databases, wirelessmobile devices such as cellular phones or personal digital assistants,wireless access points, bridges, cable modems, application accelerators,or other network devices. Data center(s) 10 may also include one or morephysical network functions (PNFs) such as physical firewalls, loadbalancers, routers, route reflectors, broadband network gateways (BNGs),mobile core network elements, and other PNFs.

In this example, TOR switches 16 and chassis switches 18 provide servers12 with redundant (multi-homed) connectivity to IP fabric 20 and serviceprovider network 7. Chassis switches 18 aggregate traffic flows andprovides connectivity between TOR switches 16. TOR switches 16 may benetwork devices that provide layer 2 (MAC) and/or layer 3 (e.g., IP)routing and/or switching functionality. TOR switches 16 and chassisswitches 18 may each include one or more processors and a memory and canexecute one or more software processes. Chassis switches 18 are coupledto IP fabric 20, which may perform layer 3 routing to route networktraffic between data center 10 and customer sites 11 by service providernetwork 7. The switching architecture of data center(s) 10 is merely anexample. Other switching architectures may have more or fewer switchinglayers, for instance. IP fabric 20 may include one or more gatewayrouters.

The term “packet flow,” “traffic flow,” or simply “flow” refers to a setof packets originating from a particular source device or endpoint andsent to a particular destination device or endpoint. A single flow ofpackets may be identified by the 5-tuple: <source network address,destination network address, source port, destination port, protocol>,for example. This 5-tuple generally identifies a packet flow to which areceived packet corresponds. An n-tuple refers to any n items drawn fromthe 5-tuple. For example, a 2-tuple for a packet may refer to thecombination of <source network address, destination network address> or<source network address, source port> for the packet.

Servers 12 may each represent a compute server or storage server. Forexample, each of servers 12 may represent a computing device, such as anx86 processor-based server, configured to operate according totechniques described herein. Servers 12 may provide Network FunctionVirtualization Infrastructure (NFVI) for an NFV architecture.

Any server of servers 12 may be configured with virtual executionelements, such as pods or virtual machines, by virtualizing resources ofthe server to provide some measure of isolation among one or moreprocesses (applications) executing on the server. “Hypervisor-based” or“hardware-level” or “platform” virtualization refers to the creation ofvirtual machines that each includes a guest operating system forexecuting one or more processes. In general, a virtual machine providesa virtualized/guest operating system for executing applications in anisolated virtual environment. Because a virtual machine is virtualizedfrom physical hardware of the host server, executing applications areisolated from both the hardware of the host and other virtual machines.Each virtual machine may be configured with one or more virtual networkinterfaces for communicating on corresponding virtual networks.

Virtual networks are logical constructs implemented on top of thephysical networks. Virtual networks may be used to replace VLAN-basedisolation and provide multi-tenancy in a virtualized data center, e.g.,an of data center(s) 10. Each tenant or an application can have one ormore virtual networks. Each virtual network may be isolated from all theother virtual networks unless explicitly allowed by security policy.

Virtual networks can be connected to and extended across physicalMulti-Protocol Label Switching (MPLS) Layer 3 Virtual Private Networks(L3VPNs) and Ethernet Virtual Private Networks (EVPNs) networks using adatacenter 10 gateway router (not shown in FIG. 1 ). Virtual networksmay also be used to implement Network Function Virtualization (NFV) andservice chaining.

Virtual networks can be implemented using a variety of mechanisms. Forexample, each virtual network could be implemented as a Virtual LocalArea Network (VLAN), Virtual Private Networks (VPN), etc. A virtualnetwork can also be implemented using two networks — the physicalunderlay network made up of IP fabric 20 and switching fabric 14 and avirtual overlay network. The role of the physical underlay network is toprovide an “IP fabric,” which provides unicast IP connectivity from anyphysical device (server, storage device, router, or switch) to any otherphysical device. The underlay network may provide uniform low-latency,non-blocking, high-bandwidth connectivity from any point in the networkto any other point in the network.

As described further below with respect to virtual router 21(illustrated as and also referred to herein as “vRouter 21”), virtualrouters running in servers 12 create a virtual overlay network on top ofthe physical underlay network using a mesh of dynamic “tunnels” amongstthemselves. These overlay tunnels can be MPLS over GRE/UDP tunnels, orVXLAN tunnels, or NVGRE tunnels, for instance. The underlay physicalrouters and switches may not store any per-tenant state for virtualmachines or other virtual execution elements, such as any Media AccessControl (MAC) addresses, IP address, or policies. The forwarding tablesof the underlay physical routers and switches may, for example, onlycontain the IP prefixes or MAC addresses of the physical servers 12.(Gateway routers or switches that connect a virtual network to aphysical network are an exception and may contain tenant MAC or IPaddresses.)

Virtual routers 21 of servers 12 often contain per-tenant state. Forexample, they may contain a separate forwarding table (arouting-instance) per virtual network. That forwarding table containsthe IP prefixes (in the case of a layer 3 overlays) or the MAC addresses(in the case of layer 2 overlays) of the virtual machines or othervirtual execution elements (e.g., pods of containers). No single virtualrouter 21 needs to contain all IP prefixes or all MAC addresses for allvirtual machines in the entire data center. A given virtual router 21only needs to contain those routing instances that are locally presenton the server 12 (i.e., which have at least one virtual executionelement present on the server 12.)

“Container-based” or “operating system” virtualization refers to thevirtualization of an operating system to run multiple isolated systemson a single machine (virtual or physical). Such isolated systemsrepresent containers, such as those provided by the open-source DOCKERContainer application or by CoreOS Rkt (“Rocket”). Like a virtualmachine, each container is virtualized and may remain isolated from thehost machine and other containers. However, unlike a virtual machine,each container may omit an individual operating system and insteadprovide an application suite and application-specific libraries. Ingeneral, a container is executed by the host machine as an isolateduser-space instance and may share an operating system and commonlibraries with other containers executing on the host machine. Thus,containers may require less processing power, storage, and networkresources than virtual machines. A group of one or more containers maybe configured to share one or more virtual network interfaces forcommunicating on corresponding virtual networks.

In some examples, containers are managed by their host kernel to allowlimitation and prioritization of resources (CPU, memory, block I/O,network, etc.) without the need for starting any virtual machines, insome cases using namespace isolation functionality that allows completeisolation of an application’s (e.g., a given container) view of theoperating environment, including process trees, networking, useridentifiers and mounted file systems. In some examples, containers maybe deployed according to Linux Containers (LXC), anoperating-system-level virtualization method for running multipleisolated Linux systems (containers) on a control host using a singleLinux kernel.

Servers 12 host virtual network endpoints for one or more virtualnetworks that operate over the physical network represented here by IPfabric 20 and switch fabric 14. Although described primarily withrespect to a data center-based switching network, other physicalnetworks, such as service provider network 7, may underlay the one ormore virtual networks.

Each of servers 12 may host one or more virtual execution elements eachhaving at least one virtual network endpoint for one or more virtualnetworks configured in the physical network. A virtual network endpointfor a virtual network may represent one or more virtual executionelements that share a virtual network interface for the virtual network.For example, a virtual network endpoint may be a virtual machine, a setof one or more containers (e.g., a pod), or another virtual executionelement(s), such as a layer 3 endpoint for a virtual network. The term“virtual execution element” encompasses virtual machines, containers,and other virtualized computing resources that provide an at leastpartially independent execution environment for applications. The term“virtual execution element” may also encompass a pod of one or morecontainers. Virtual execution elements may represent applicationworkloads. As shown in FIG. 1 , server 12A hosts one virtual networkendpoint in the form of pod 22 having one or more containers. However, aserver 12 may execute as many virtual execution elements as is practicalgiven hardware resource limitations of the server 12. Each of thevirtual network endpoints may use one or more virtual network interfacesto perform packet I/O or otherwise process a packet. For example, avirtual network endpoint may use one virtual hardware component (e.g.,an SR-IOV virtual function) enabled by NIC 13A to perform packet I/O andreceive/send packets on one or more communication links with TOR switch16A. Other examples of virtual network interfaces are described below.

Servers 12 each includes at least one network interface card (NIC) 13,which each includes at least one interface to exchange packets with TORswitches 16 over a communication link. For example, server 12A includesNIC 13A. Any of NICs 13 may provide one or more virtual hardwarecomponents 21 for virtualized input/output (I/O). A virtual hardwarecomponent for I/O maybe a virtualization of the physical NIC (the“physical function”). For example, in Single Root I/O Virtualization(SR-IOV), which is described in the Peripheral Component InterfaceSpecial Interest Group SR-IOV specification, the PCIe Physical Functionof the network interface card (or “network adapter”) is virtualized topresent one or more virtual network interfaces as “virtual functions”for use by respective endpoints executing on the server 12. In this way,the virtual network endpoints may share the same PCIe physical hardwareresources and the virtual functions are examples of virtual hardwarecomponents 21. As another example, one or more servers 12 may implementVirtio, a para-virtualization framework available, e.g., for the LinuxOperating System, that provides emulated NIC functionality as a type ofvirtual hardware component to provide virtual network interfaces tovirtual network endpoints. As another example, one or more servers 12may implement Open vSwitch to perform distributed virtual multilayerswitching between one or more virtual NICs (vNICs) for hosted virtualmachines, where such vNICs may also represent a type of virtual hardwarecomponent that provide virtual network interfaces to virtual networkendpoints. In some instances, the virtual hardware components arevirtual I/O (e.g., NIC) components. In some instances, the virtualhardware components are SR-IOV virtual functions. In some examples, anyserver of servers 12 may implement a Linux bridge that emulates ahardware bridge and forwards packets among virtual network interfaces ofthe server or between a virtual network interface of the server and aphysical network interface of the server. For Docker implementations ofcontainers hosted by a server, a Linux bridge or other operating systembridge, executing on the server, that switches packets among containersmay be referred to as a “Docker bridge.” The term “virtual router” asused herein may encompass a Contrail or Tungsten Fabric virtual router,Open vSwitch (OVS), an OVS bridge, a Linux bridge, Docker bridge, orother device and/or software that is located on a host device andperforms switching, bridging, or routing packets among virtual networkendpoints of one or more virtual networks, where the virtual networkendpoints are hosted by one or more of servers 12.

Any of NICs 13 may include an internal device switch to switch databetween virtual hardware components associated with the NIC. Forexample, for an SR-IOV-capable NIC, the internal device switch may be aVirtual Ethernet Bridge (VEB) to switch between the SR-IOV virtualfunctions and, correspondingly, between endpoints configured to use theSR-IOV virtual functions, where each endpoint may include a guestoperating system. Internal device switches may be alternatively referredto as NIC switches or, for SR-IOV implementations, SR-IOV NIC switches.Virtual hardware components associated with NIC 13A may be associatedwith a layer 2 destination address, which may be assigned by the NIC 13Aor a software process responsible for configuring NIC 13A. The physicalhardware component (or “physical function” for SR-IOV implementations)is also associated with a layer 2 destination address.

One or more of servers 12 may each include a virtual router 21 thatexecutes one or more routing instances for corresponding virtualnetworks within data center 10 to provide virtual network interfaces androute packets among the virtual network endpoints. Each of the routinginstances may be associated with a network forwarding table. Each of therouting instances may represent a virtual routing and forwardinginstance (VRF) for an Internet Protocol-Virtual Private Network(IP-VPN). Packets received by virtual router 21 of server 12A, forinstance, from the underlying physical network fabric of data center 10(i.e., IP fabric 20 and switch fabric 14) may include an outer header toallow the physical network fabric to tunnel the payload or “innerpacket” to a physical network address for a network interface card 13Aof server 12A that executes the virtual router. The outer header mayinclude not only the physical network address of the network interfacecard 13A of the server but also a virtual network identifier such as aVxLAN tag or Multiprotocol Label Switching (MPLS) label that identifiesone of the virtual networks as well as the corresponding routinginstance executed by virtual router 21. An inner packet includes aninner header having a destination network address that conforms to thevirtual network addressing space for the virtual network identified bythe virtual network identifier.

Virtual routers 21 terminate virtual network overlay tunnels anddetermine virtual networks for received packets based on tunnelencapsulation headers for the packets, and forwards packets to theappropriate destination virtual network endpoints for the packets. Forserver 12A, for example, for each of the packets outbound from virtualnetwork endpoints hosted by server 12A (e.g., pod 22), virtual router 21attaches a tunnel encapsulation header indicating the virtual networkfor the packet to generate an encapsulated or “tunnel” packet, andvirtual router 21 outputs the encapsulated packet via overlay tunnelsfor the virtual networks to a physical destination computing device,such as another one of servers 12. As used herein, virtual router 21 mayexecute the operations of a tunnel endpoint to encapsulate inner packetssourced by virtual network endpoints to generate tunnel packets anddecapsulate tunnel packets to obtain inner packets for routing to othervirtual network endpoints.

In some examples, virtual router 21 may be a kernel-based and execute aspart of the kernel of an operating system of server 12A.

In some examples, virtual router 21 may be a Data Plane Development Kit(DPDK)-enabled virtual router. In such examples, virtual router 21 usesDPDK as a data plane. In this mode, virtual router 21 runs as a userspace application that is linked to the DPDK library (not shown). Thisis a performance version of a virtual router and is commonly used bytelecommunications companies, where the VNFs are often DPDK-basedapplications. The performance of virtual router 21 as a DPDK virtualrouter can achieve ten times higher throughput than a virtual routeroperating as a kernel-based virtual router. The physical interface isused by DPDK’s poll mode drivers (PMDs) instead of Linux kernel’sinterrupt-based drivers.

A user-I/O (UIO) kernel module, such as vfio or uio_pci_generic, may beused to expose a physical network interface’s registers into user spaceso that they are accessible by the DPDK PMD. When NIC 13A is bound to aUIO driver, it is moved from Linux kernel space to user space andtherefore no longer managed nor visible by the Linux OS. Consequently,it is the DPDK application (i.e., virtual router 21A in this example)that fully manages the NIC 13. This includes packets polling, packetsprocessing, and packets forwarding. User packet processing steps may beperformed by the virtual router 21 DPDK data plane with limited or noparticipation by the kernel (kernel not shown in FIG. 1 ). The nature ofthis “polling mode” makes the virtual router 21 DPDK data plane packetprocessing/forwarding much more efficient as compared to the interruptmode, particularly when the packet rate is high. There are limited or nointerrupts and context switching during packet I/O.

Additional details of an example of a DPDK vRouter are found in “DAYONE: CONTRAIL DPDK vROUTER,” 2021, Kiran KN et al., Juniper Networks,Inc., which is incorporated by reference herein in its entirety.

Computing infrastructure 8 implements an automation platform forautomating deployment, scaling, and operations of virtual executionelements across servers 12 to provide virtualized infrastructure forexecuting application workloads and services. In some examples, theplatform may be a container orchestration system that provides acontainer-centric infrastructure for automating deployment, scaling, andoperations of containers to provide a container-centric infrastructure.“Orchestration,” in the context of a virtualized computinginfrastructure generally refers to provisioning, scheduling, andmanaging virtual execution elements and/or applications and servicesexecuting on such virtual execution elements to the host serversavailable to the orchestration platform. Container orchestration,specifically, permits container coordination and refers to thedeployment, management, scaling, and configuration, e.g., of containersto host servers by a container orchestration platform. Example instancesof orchestration platforms include Kubernetes (a container orchestrationsystem), Docker swarm, Mesos/Marathon, OpenShift, OpenStack, VMware, andAmazon ECS.

Elements of the automation platform of computing infrastructure 8include at least servers 12, orchestrator 23, and network controller 24.Containers may be deployed to a virtualization environment using acluster-based framework in which a cluster master node of a clustermanages the deployment and operation of containers to one or morecluster minion nodes of the cluster. The terms “master node” and “minionnode” used herein encompass different orchestration platform terms foranalogous devices that distinguish between primarily management elementsof a cluster and primarily container hosting devices of a cluster. Forexample, the Kubernetes platform uses the terms “cluster master” and“minion nodes,” while the Docker Swarm platform refers to clustermanagers and cluster nodes.

Orchestrator 23 and network controller 24 may execute on separatecomputing devices, execute on the same computing device. Each oforchestrator 23 and network controller 24 may be a distributedapplication that executes on one or more computing devices. Orchestrator23 and network controller 24 may implement respective master nodes forone or more clusters each having one or more minion nodes implemented byrespective servers 12 (also referred to as “compute nodes”).

In general, network controller 24 controls the network configuration ofthe data center 10 fabric to, e.g., establish one or more virtualnetworks for packetized communications among virtual network endpoints.Network controller 24 provides a logically and in some cases physicallycentralized controller for facilitating operation of one or more virtualnetworks within data center 10. In some examples, network controller 24may operate in response to configuration input received fromorchestrator 23 and/or an administrator/operator. Additional informationregarding example operations of a network controller 24 operating inconjunction with other devices of data center 10 or othersoftware-defined network is found in International Application NumberPCT/US2013/044378, filed Jun. 5, 2013, and entitled “PHYSICAL PATHDETERMINATION FOR VIRTUAL NETWORK PACKET FLOWS;” and in U.S. Pat. Appln.No. 14/226,509, filed Mar. 26, 2014, and entitled “Tunneled PacketAggregation for Virtual Networks,” each which is incorporated byreference as if fully set forth herein.

In general, orchestrator 23 controls the deployment, scaling, andoperations of containers across clusters of servers 12 and providingcomputing infrastructure, which may include container-centric computinginfrastructure. Orchestrator 23 and, in some cases, network controller24 may implement respective cluster masters for one or more Kubernetesclusters. As an example, Kubernetes is a container management platformthat provides portability across public and private clouds, each ofwhich may provide virtualization infrastructure to the containermanagement platform. Example components of a Kubernetes orchestrationsystem are described below with respect to FIG. 3 .

Kubernetes operates using a variety of Kubernetes objects — entitieswhich represent a state of a Kubernetes cluster. Kubernetes objects mayinclude any combination of names, namespaces, labels, annotations, fieldselectors, and recommended labels. For example, a Kubernetes cluster mayinclude one or more “namespace” objects. Each namespace of a Kubernetescluster is isolated from other namespaces of the Kubernetes cluster.Namespace objects may include at least one of organization, security,and performance of a Kubernetes cluster. As an example, a pod may beassociated with a namespace, consequently associating the pod withcharacteristics (e.g., virtual networks) of the namespace. This featuremay enable a plurality of newly-created pods to organize by associatingthe pods with a common set of characteristics. A namespace can becreated according to namespace specification data that definescharacteristics of the namespace, including a namespace name. In oneexample, a namespace might be named “Namespace A” and each newly-createdpod may be associated with a set of characteristics denoted by“Namespace A.” Additionally, Kubernetes includes a “default” namespace.If a newly-created pod does not specify a namespace, the newly-createdpod may associate with the characteristics of the “default” namespace.

Namespaces may enable one Kubernetes cluster to be used by multipleusers, teams of users, or a single user with multiple applications.Additionally, each user, team of users, or application may be isolatedwithin a namespace from every other user of the cluster. Consequently,each user of a Kubernetes cluster within a namespace operates as if itwere the sole user of the Kubernetes cluster. Multiple virtual networksmay be associated with a single namespace. As such, a pod that belongsto a particular namespace has the ability to access each virtual networkof the virtual networks that is associated with the namespace, includingother pods that serve as virtual network endpoints of the group ofvirtual networks.

In one example, pod 22 is a Kubernetes pod and an example of a virtualnetwork endpoint. A pod is a group of one or more logically-relatedcontainers (not shown in FIG. 1 ), the shared storage for thecontainers, and options on how to run the containers. Where instantiatedfor execution, a pod may alternatively be referred to as a “podreplica.” Each container of pod 22 is an example of a virtual executionelement. Containers of a pod are always co-located on a single server,co-scheduled, and run in a shared context. The shared context of a podmay be a set of Linux namespaces, cgroups, and other facets ofisolation. Within the context of a pod, individual applications mighthave further sub-isolations applied. Typically, containers within a podhave a common IP address and port space and are able to detect oneanother via the localhost. Because they have a shared context,containers within a pod are also communicate with one another usinginter-process communications (IPC). Examples of IPC include SystemVsemaphores or POSIX shared memory. Generally, containers that aremembers of different pods have different IP addresses and are unable tocommunicate by IPC in the absence of a configuration for enabling thisfeature. Containers that are members of different pods instead usuallycommunicate with each other via pod IP addresses.

Server 12A includes a container platform 19 for running containerizedapplications, such as those of pod 22. Container platform 19 receivesrequests from orchestrator 23 to obtain and host, in server 12A,containers. Container platform 19 obtains and executes the containers.

Container network interface (CNI) 17 configures virtual networkinterfaces for virtual network endpoints. The orchestrator 23 andcontainer platform 19 use CNI 17 to manage networking for pods,including pod 22. For example, CNI 17 creates virtual network interfacesto connect pods to virtual router 21 and enables containers of such podsto communicate, via the virtual network interfaces, to other virtualnetwork endpoints over the virtual networks. CNI 17 may, for example,insert a virtual network interface for a virtual network into thenetwork namespace for containers in pod 22 and configure (or request toconfigure) the virtual network interface for the virtual network invirtual router 21 such that virtual router 21 is configured to sendpackets received from the virtual network via the virtual networkinterface to containers of pod 22 and to send packets received via thevirtual network interface from containers of pod 22 on the virtualnetwork. CNI 17 may assign a network address (e.g., a virtual IP addressfor the virtual network) and may set up routes for the virtual networkinterface. In Kubemetes, by default all pods can communicate with allother pods without using network address translation (NAT). In somecases, the orchestrator 23 and network controller 24 create a servicevirtual network and a pod virtual network that are shared by allnamespaces, from which service and pod network addresses are allocated,respectively. In some cases, all pods in all namespaces that are spawnedin the Kubemetes cluster may be able to communicate with one another,and the network addresses for all of the pods may be allocated from apod subnet that is specified by the orchestrator 23. When a user createsan isolated namespace for a pod, orchestrator 23 and network controller24 may create a new pod virtual network and new shared service virtualnetwork for the new isolated namespace. Pods in the isolated namespacethat are spawned in the Kubernetes cluster draw network addresses fromthe new pod virtual network, and corresponding services for such podsdraw network addresses from the new service virtual network

CNI 17 may represent a library, a plugin, a module, a runtime, or otherexecutable code for server 12A. CNI 17 may conform, at least in part, tothe Container Network Interface (CNI) specification or the rktNetworking Proposal. CNI 17 may represent a Contrail, OpenContrail,Multus, Calico, cRPD, or other CNI. CNI 17 may alternatively be referredto as a network plugin or CNI plugin or CNI instance. Separate CNIs maybe invoked by, e.g., a Multus CNI to establish different virtual networkinterfaces for pod 22.

CNI 17 may be invoked by orchestrator 23. For purposes of the CNIspecification, a container can be considered synonymous with a Linuxnetwork namespace. What unit this corresponds to depends on a particularcontainer runtime implementation: for example, in implementations of theapplication container specification such as rkt, each pod runs in aunique network namespace. In Docker, however, network namespacesgenerally exist for each separate Docker container. For purposes of theCNI specification, a network refers to a group of entities that areuniquely addressable and that can communicate amongst each other. Thiscould be either an individual container, a machine/server (real orvirtual), or some other network device (e.g. a router). Containers canbe conceptually added to or removed from one or more networks. The CNIspecification specifies a number of considerations for a conformingplugin (“CNI plugin”).

Pod 22 includes one or more containers. In some examples, pod 22includes a containerized DPDK workload that is designed to use DPDK toaccelerate packet processing, e.g., by exchanging data with othercomponents using DPDK libraries. Virtual router 21 may execute as acontainerized DPDK workload in some examples.

Pod 22 is configured with virtual network interface 26 for sending andreceiving packets with virtual router 21. Virtual network interface 26may be a default interface for pod 22. Pod 22 may implement virtualnetwork interface 26 as an Ethernet interface (e.g., named “eth0”) whilevirtual router 21 may implement virtual network interface 26 as a tapinterface, virtio-user interface, or other type of interface.

Pod 22 and virtual router 21 exchange data packets using virtual networkinterface 26. Virtual network interface 26 may be a DPDK interface. Pod22 and virtual router 21 may set up virtual network interface 26 usingvhost. Pod 22 may operate according to an aggregation model. Pod 22 mayuse a virtual device, such as a virtio device with a vhost-user adapter,for user space container inter-process communication for virtual networkinterface 26.

CNI 17 may configure, for pod 22, in conjunction with one or more othercomponents shown in FIG. 1 , virtual network interface 26. Any of thecontainers of pod 22 may utilize, i.e., share, virtual network interface26 of pod 22.

Virtual network interface 26 may represent a virtual ethernet (“veth”)pair, where each end of the pair is a separate device (e.g., aLinux/Unix device), with one end of the pair assigned to pod 22 and oneend of the pair assigned to virtual router 21. The veth pair or an endof a veth pair are sometimes referred to as “ports”. A virtual networkinterface may represent a macvlan network with media access control(MAC) addresses assigned to pod 22 and to virtual router 21 forcommunications between containers of pod 22 and virtual router 21.Virtual network interfaces may alternatively be referred to as virtualmachine interfaces (VMIs), pod interfaces, container network interfaces,tap interfaces, veth interfaces, or simply network interfaces (inspecific contexts), for instance.

In the example server 12A of FIG. 1 , pod 22 is a virtual networkendpoint in one or more virtual networks. Orchestrator 23 may store orotherwise manage configuration data for application deployments thatspecifies a virtual network and specifies that pod 22 (or the one ormore containers therein) is a virtual network endpoint of the virtualnetwork. Orchestrator 23 may receive the configuration data from a user,operator/administrator, or other machine system, for instance.

As part of the process of creating pod 22, orchestrator 23 requests thatnetwork controller 24 create respective virtual network interfaces forone or more virtual networks (indicated in the configuration data). Pod22 may have a different virtual network interface for each virtualnetwork to which it belongs. For example, virtual network interface 26may be a virtual network interface for a particular virtual network.Additional virtual network interfaces (not shown) may be configured forother virtual networks. Network controller 24 processes the request togenerate interface configuration data for virtual network interfaces forthe pod 22. Interface configuration data may include a container or podunique identifier and a list or other data structure specifying, foreach of the virtual network interfaces, network configuration data forconfiguring the virtual network interface. Network configuration datafor a virtual network interface may include a network name, assignedvirtual network address, MAC address, and/or domain name server values.An example of interface configuration data in JavaScript Object Notation(JSON) format is below.

Network controller 24 sends interface configuration data to server 12Aand, more specifically in some cases, to virtual router 21. To configurea virtual network interface for pod 22, orchestrator 23 may invoke CNI17. CNI 17 obtains the interface configuration data from virtual router21 and processes it. CNI 17 creates each virtual network interfacespecified in the interface configuration data. For example, CNI 17 mayattach one end of a veth pair implementing management interface 26 tovirtual router 21 and may attach the other end of the same veth pair topod 22, which may implement it using virtio-user.

The following is example interface configuration data for pod 22 forvirtual network interface 26.

[{   // virtual network interface 26   “id”: “fe4bab62-a716-11e8-abd5-0cc47a698428”,   “instance-id”: “fe3edca5-a716-11e8-822c-0cc47a698428”,   “ip-address”: “10.47.255.250”,    “plen”: 12,   “vn-id”: “56dda39c-5e99-4a28-855e-6ce378982888”,   “vm-project-id”: “00000000-0000-0000-0000-000000000000”,   “mac-address”: “02:fe:4b:ab:62:a7”,   “system-name”: “tapeth0fe3edca”,    “rx-vlan-id”: 65535,   “tx-vlan-id”: 65535,    “vhostuser-mode”: 0,   “v6-ip-address”: “::”,    “v6-plen”: ,    “v6-dns-server”: “::”,   “v6-gateway”: “::”,    “dns-server”: “10.47.255.253”,   “gateway”: “10.47.255.254”,   “author”: “/usr/bin/contrail-vrouter-agent”,   “time”: “426404:56:19.863169” }]

A conventional CNI plugin is invoked by a container platform/runtime,receives an Add command from the container platform to add a containerto a single virtual network, and such a plugin may subsequently beinvoked to receive a Del(ete) command from the container/runtime andremove the container from the virtual network. The term “invoke” mayrefer to the instantiation, as executable code, of a software componentor module in memory for execution by processing circuitry.

In accordance with techniques described in this disclosure, networkcontroller 24 is a cloud-native, distributed network controller forsoftware-defined networking (SDN) that is implemented using one or moreconfiguration nodes 30 and one or more control nodes 32. Each ofconfiguration nodes 30 may itself be implemented using one or morecloud-native, component microservices. Each of control nodes 32 mayitself be implemented using one or more cloud-native, componentmicroservices.

In some examples, and as described in further detail below,configuration nodes 30 may be implemented by extending the nativeorchestration platform to support custom resources for the orchestrationplatform for software-defined networking and, more specifically, forproviding northbound interfaces to orchestration platforms to supportintent-driven / declarative creation and managing of virtual networksby, for instance, configuring virtual network interfaces for virtualexecution elements, configuring underlay networks connecting servers 12,configuring overlay routing functionality including overlay tunnels forthe virtual networks and overlay trees for multicast layer 2 and layer3.

Network controller 24, as part of the SDN architecture illustrated inFIG. 1 , may be multi-tenant aware and support multi-tenancy fororchestration platforms. For example, network controller 24 may supportKubernetes Role Based Access Control (RBAC) constructs, local identityaccess management (IAM) and external IAM integrations. Networkcontroller 24 may also support Kubernetes-defined networking constructsand advanced networking features like virtual networking, BGPaaS,networking policies, service chaining and other telco features. Networkcontroller 24 may support network isolation using virtual networkconstructs and support layer 3 networking.

To interconnect multiple virtual networks, network controller 24 may use(and configure in the underlay and/or virtual routers 21) networkpolicies, referred to as Virtual Network Policy (VNP) and alternativelyreferred to herein as Virtual Network Router or Virtual NetworkTopology. The VNP defines connectivity policy between virtual networks.A single network controller 24 may support multiple Kubernetes clusters,and VNP thus allows connecting multiple virtual networks in a namespace,Kubernetes cluster and across Kubernetes clusters. VNP may also extendto support virtual network connectivity across multiple instances ofnetwork controller 24.

Network controller 24 may enable multi layers of security using networkpolicies. The Kubernetes default behavior is for pods to communicatewith one another. In order to apply network security policies, the SDNarchitecture implemented by network controller 24 and virtual router 21may operate as a CNI for Kubernetes through CNI 17. For layer 3,isolation occurs at the network level and virtual networks operate atL3. Virtual networks are connected by policy. The Kubernetes nativenetwork policy provides security at layer 4. The SDN architecture maysupport Kubernetes network policies. Kubernetes network policy operatesat the Kubernetes namespace boundary. The SDN architecture may addcustom resources for enhanced network policies. The SDN architecture maysupport application-based security. (These security policies can in somecases be based upon metatags to apply granular security policy in anextensible manner.) For layer 4+, the SDN architecture may in someexamples support integration with containerized security devices and/orIstio and may provide encryption support.

Network controller 24, as part of the SDN architecture illustrated inFIG. 1 , may support multi-cluster deployments, which is important fortelco cloud and high-end enterprise use cases. The SDN architecture maysupport multiple Kubernetes clusters, for instance. A Cluster API can beused to support life cycle management of Kubernetes clusters. KubefedV2can be used for configuration nodes 32 federation across Kubernetesclusters. Cluster API and KubefedV2 are optional components forsupporting a single instance of a network controller 24 supportingmultiple Kubernetes clusters.

The SDN architecture may provide insights at infrastructure, cluster,and application using web user interface and telemetry components.Telemetry nodes may be cloud-native and include microservices to supportinsights.

As a result of the above features and others that will be describedelsewhere herein, computing infrastructure 8 implements an SDNarchitecture that is cloud-native and may present one or more of thefollowing technical advantages. For example, network controller 24 is acloud-native, lightweight distributed application with a simplifiedinstallation footprint. This also facilitates easier and modular upgradeof the various component microservices for configuration node(s) 30 andcontrol node(s) 32 (as well as any other components of other example ofa network controller described in this disclosure). The techniques mayfurther enable optional cloud-native monitoring (telemetry) and userinterfaces, a high-performance data plane for containers using aDPDK-based virtual router connecting to DPDK-enabled pods, andcloud-native configuration management that in some cases leverages aconfiguration framework for existing orchestration platforms, such asKubernetes or Openstack. As a cloud-native architecture, networkcontroller 24 is a scalable and elastic architecture to address andsupport multiple clusters. Network controller 24 in some cases may alsosupport scalability and performance requirements for key performanceindicators (KPIs).

An SDN architecture having features and technical advantages such asthose described herein can be used to implement cloud-native telcoclouds to support, for instance, 5G mobile networking (and subsequentgenerations) and edge computing, as well as enterprise Kubernetesplatforms including, for instance, high performance cloud-nativeapplication hosting. Telco cloud applications are rapidly moving towardscontainerized, cloud-native approaches. 5G fixed and mobile networks aredriving the requirement to deploy workloads as microservices withsignificant disaggregation, particularly in the 5G Next-Gen RAN (5GNR).The 5G NextGen Core (5GNC) is likely to be deployed as a set ofmicroservices-based applications corresponding to each of the differentcomponents described by the 3GPP. When viewed as groups of microservicesdelivering applications, it 5GNC is likely to be a highly complexcombination of pods with complex networking, security, and policyrequirements. The cloud-native SDN architecture described herein, havingwell-defined constructs for networking, security, and policy, can beleveraged for this use case. Network controller 24 may provide therelevant APIs to be able to create these complex constructs.

Likewise, the user plane function (UPF) within the 5GNC will be anultra-high-performance application. It may be delivered as a highlydistributed set of high-performance pods. The SDN architecture describedherein may be able to offer very high throughput data plane (both interms of bits per section (bps) and packets per second (pps)).Integration with a DPDK virtual router with recent performanceenhancements, eBPF, and with SmartNIC will be assist with achieving thethroughput required. A DPDK-based virtual router is described in furtherdetail in U.S. Application No. 17/649,632, filed Feb. 1, 2022, entitled“CONTAINERIZED ROUTER WITH VIRTUAL NETWORKING”, which is incorporatedherein by reference in its entirety.

High performance processing is likely to be also relevant in the GiLANas workloads there are migrated from more traditional virtualizedworkloads to containerized microservices. In the data plane of both theUPF and the GiLAN services, such as GiLAN firewall, intrusion detectionand prevention, virtualized IP multimedia subsystem (vIMS) voice/video,and so forth, the throughput will be high and sustained both in terms ofbps and pps. For the control plane of 5 GNC functions, such as Accessand Mobility Management Function (AMF), Session Management Function(SMF), etc., as well as for some GiLAN services (e.g., IMS), while theabsolute volume of traffic in terms of bps may be modest, thepredominance of small packets means that pps will remain high. In someexamples, the SDN controller and data plane provide multi-millionpackets per second per virtual router 21, as implemented on servers 12.In the 5G radio access network (RAN), to move away from the proprietaryvertically integrated RAN stacks provided by legacy radio vendors, OpenRAN decouples the RAN hardware and software in a number of componentsincluding non-RT Radio Intelligent Controller (RIC), near-real-time RIC,centralized unit (CU) control plane and user plane (CU-CP and CU-UP),distributed unit (DU), and radio unit (RU). Software components aredeployed on commodity server architectures supplemented withprogrammable accelerators where necessary. The SDN architecturedescribed herein may support the O-RAN specifications.

Edge compute is likely to be primarily targeted at two different usecases. The first will be as a support for containerized telcoinfrastructure (e.g. 5G RAN, UPF, Security functions) and the secondwill be for containerized service workloads, both from the telco as wellas from third parties such as vendors or enterprise customers. In bothcases, edge compute is effectively a special case of the GiLAN, wheretraffic is broken out for special handling at highly distributedlocations. In many cases, these locations will have limited resources(power, cooling, space). The SDN architecture described herein may bewell-suited to support the requirement of a very lightweight footprint,may support compute and storage resources in sites remote from theassociated control functions, and may be location-aware in the way inwhich workloads and storage are deployed. Some sites may have as few asone or two compute nodes delivering a very specific set of services to ahighly localized set of users or other services. There is likely to be ahierarchy of sites where the central sites are densely connected withmany paths, regional sites are multiply connected with two to fouruplink paths and the remote edge sites may have connections to only oneor two upstream sites. This calls for extreme flexibility in the way inwhich the SDN architecture may be deployed and the way (and location) inwhich tunneled traffic in the overlay is terminated and bound into thecore transport network (SRv6, MPLS, etc.). Likewise, in sites that hosttelco cloud infrastructure workloads, the SDN architecture describedherein may support specialized hardware (GPU, SmartNIC, etc.) requiredby high-performance workloads. There may also be workloads that requireSR-IOV. As such, the SDN architecture may also support the creation ofVTEPs at the ToR and linking that back into the overlay as VXLAN.

It is expected that there will be a mix of fully distributed Kubernetesmicro clusters where each site runs its own master(s), and the SDNarchitecture may support Remote Compute-like scenarios.

For use cases involving an enterprise Kubernetes platform,high-performance cloud-native applications power financial servicesplatforms, online gaming services, and hosted application serviceproviders. The cloud platforms that deliver these applications mustprovide high performance, resilience against failures, with highsecurity and visibility. The applications hosted on these platforms tendto be developed in-house. The application developers and platform ownerswork with the infrastructure teams to deploy and operate instances ofthe organization’s applications. These applications tend to require highthroughput (>20 Gbps per server), and low latency. Some applications mayalso use multicast for signaling or payload traffic. Additionalhardware, and network infrastructure may be leveraged to ensureavailability. Applications and microservices will leverage namespaceswithin the cluster for partitioning. Isolation between namespaces iscritical in high-security environments. While default deny policies arethe standard posture in zero-trust application deployment environments,additional network segmentation using virtual routing and forwardinginstances (VRFs) adds an additional layer of security and allows for theuse of overlapping network ranges. Overlapping network ranges are a keyrequirement for managed application hosting environments, which tend tostandardize on a set of reachable endpoints for all managed customers.

Complex microservice-based applications tend to leverage complex networkfilters. The SDN architecture described herein may deliver highperformance firewall filtering at scale. Such filtering can exhibitconsistent forwarding performance, with less latency degradationregardless of rule-set length or sequence. Some customers may also havesome of the same regulatory pressures as telcos with respect to theseparation of applications, not just at the network layer, but also inthe kernel. Financials, but also others have the requirement for dataplane encryption, particularly when running on public cloud. In someexamples, the SDN architecture described herein may include features forsatisfying these requirements.

In some examples, the SDN architecture may provide GitOps-friendly UXfor strict change management controls, auditing and reliability ofmaking changes in production several times per day, even hundreds oftimes per day when the SDN architecture is automated through anapplication dev/test/stage/prod continuous integration/continuousdevelopment (CI/CD) pipeline.

FIG. 2 is a block diagram illustrating an example of a cloud-native SDNarchitecture for cloud native networking, in accordance with techniquesof this disclosure. SDN architecture 200 is illustrated in a manner thatabstracts underlying connectivity among the various components. In thisexample, network controller 24 of SDN architecture 200 includesconfiguration nodes 230A-230N (“configuration nodes” or “config nodes”and collectively, “configuration nodes 230”) and control nodes 232A-232K(collectively, “control nodes 232”). Configuration nodes 230 and controlnodes 232 may represent examples implementations of configuration nodes30 and control nodes 32 of FIG. 1 , respectively. Configuration nodes230 and control nodes 232, although illustrated as separate from servers12, may be executed as one or more workloads on servers 12.

Configuration nodes 230 offer northbound, REpresentation State Transfer(REST) interfaces to support intent-driven configuration of SDNarchitecture 200. Example platforms and applications that may be used topush intents to configuration nodes 230 include virtual machineorchestrator 240 (e.g., Openstack), container orchestrator 242 (e.g.,Kubernetes), user interface 242, or other one or more application(s)246. In some examples, SDN architecture 200 has Kubernetes as its baseplatform.

SDN architecture 200 is divided into a configuration plane, controlplane, and data plane, along with an optional telemetry (or analytics)plane. The configuration plane is implemented with horizontally scalableconfiguration nodes 230, the control plane is implemented withhorizontally scalable control nodes 232, and the data plane isimplemented with compute nodes.

At a high level, configuration nodes 230 uses configuration store 224 tomanage the state of configuration resources of SDN architecture 200. Ingeneral, a configuration resource (or more simply “resource”) is a namedobject schema that includes data and/or methods that describe the customresource, and an application programming interface (API) is defined forcreating and manipulating the data through an API server. A kind is thename of an object schema. Configuration resources may include Kubernetesnative resources, such as Pod, Ingress, Configmap, Service, Role,Namespace, Node, Networkpolicy, or LoadBalancer. In accordance withtechniques of this disclosure, configuration resources also includecustom resources, which are used to extend the Kubernetes platform bydefining an application program interface (API) that may not beavailable in a default installation of the Kubernetes platform. In theexample of SDN architecture 200, custom resources may describe physicalinfrastructure, virtual infrastructure, configurations, and/or otherresources of SDN architecture 200. As part of the configuration andoperation SDN architecture 200, various custom resources may beinstantiated. Instantiated resources (whether native or custom) may bereferred to as objects or as instances of the resource, which arepersistent entities in SDN architecture 200 that represent an intent(desired state) and the status (actual state) of the SDN architecture200. Configuration nodes 230 provide an aggregated API for performingoperations on (i.e., creating, reading, updating, and deleting)configuration resources of SDN architecture 200 in configuration store224. Load balancer 226 represents one or more load balancer objects thatload balance configuration requests among configuration nodes 230.Configuration store 224 may represent one or more etcd databases.Configuration nodes 230 may be implemented using Nginx.

SDN architecture 200 may provide networking for both Openstack andKubernetes. Openstack uses a plugin architecture to support networking.With virtual machine orchestrator 240 that is Openstack, the Openstacknetworking plugin driver converts Openstack configuration objects to SDNarchitecture 200 configuration objects (resources). Compute nodes runOpenstack nova to bring up virtual machines.

With container orchestrator 242 that is Kubernetes, SDN architecture 200functions as a Kubernetes CNI. As noted above, Kubernetes nativeresources (pod, services, ingress, external load balancer, etc.) may besupported, and SDN architecture 200 may support custom resources forKubemetes for advanced networking and security for SDN architecture 200.

Configuration nodes 230 offer REST watch to control nodes 232 to watchfor configuration resource changes, which control nodes 232 effectwithin the computing infrastructure. Control nodes 232 receiveconfiguration resource data from configuration nodes 230, by watchingresources, and build a full configuration graph. A given one of controlnodes 232 consumes configuration resource data relevant for the controlnodes and distributes required configurations to the compute nodes(servers 12) via control interfaces 254 to the control plane aspect ofvirtual router 21 (i.e., the virtual router agent -- not shown in FIG. 1). Any of compute nodes 232 may receive only a partial graph, as isrequired for processing. Control interfaces 254 may be XMPP. The numberof configuration nodes 230 and control nodes 232 that are deployed maybe a function of the number of clusters supported. To support highavailability, the configuration plane may include 2N+1 configurationnodes 230 and 2N control nodes 232.

Control nodes 232 distributes routes among the compute nodes. Controlnode 232 uses internal Border Gateway Protocol (iBGP) to exchange routesamong control nodes 232, and control nodes 232 may peer with anyexternal BGP supported gateways or other routers. Control nodes 232 mayuse a route reflector.

Pods 250 and virtual machines 252 are examples of workloads that may bedeployed to the compute nodes by virtual machine orchestrator 240 orcontainer orchestrator 242 and interconnected by SDN architecture 200using one or more virtual networks.

FIG. 3 is a block diagram illustrating another view of components of SDNarchitecture 200 and in further detail, in accordance with techniques ofthis disclosure. Configuration nodes 230, control nodes, 232, and userinterface 244 are illustrated with their respective componentmicroservices for implementing network controller 24 and SDNarchitecture 200 as a cloud-native SDN architecture. Each of thecomponent microservices may be deployed to compute nodes.

FIG. 3 illustrates a single cluster divided into network controller 24,user interface 244, compute (servers 12), and telemetry 260 features.Configuration nodes 230 and control nodes 232 together form networkcontroller 24.

Configuration nodes 230 may include component microservices API server300 (or “Kubernetes API server 300” — corresponding controller 406 notshown in FIG. 3 ), custom API server 301, custom resource controller302, and SDN controller manager 303 (sometimes termed “kube-manager” or“SDN kube-manager” where the orchestration platform for networkcontroller 24 is Kubernetes). Contrail-kube-manager is an example of SDNcontroller manager 303. Configuration nodes 230 extend the API server300 interface with a custom API server 301 to form an aggregation layerto support a data model for SDN architecture 200. SDN architecture 200configuration intents may be custom resources, as described above.

Control nodes 232 may include component microservice control 320.Control 320 performs configuration distribution and route learning anddistribution, as described above with respect to FIG. 2 .

Compute nodes are represented by servers 12. Each compute node includesa virtual router agent 316 and virtual router forwarding component(vRouter) 318. Either or both of virtual router agent 316 and vRouter318 may be component microservices. In general, virtual router agent 316performs control related functions. Virtual router agent 316 receivesconfiguration data from control nodes 232 and converts the configurationdata to forwarding information for vRouter 318. Virtual router agent 316may also performs firewall rule processing, set up flows for vRouter318, and interface with orchestration plugins (CNI for Kubernetes andNova plugin for Openstack). Virtual router agent 316 generates routes asworkloads (Pods or VMs) are brought up on the compute node, and virtualrouter 316 exchanges such routes with control nodes 232 for distributionto other compute nodes (control nodes 232 distribute the routes amongcontrol nodes 232 using BGP). Virtual router agent 316 also withdrawsroutes as workloads are terminated. vRouter 318 may support one or moreforwarding modes, such as kernel mode, DPDK, SmartNIC offload, and soforth. In some examples of container architectures or virtual machineworkloads, compute nodes may be either Kubemetes worker/minion nodes orOpenstack nova-compute nodes, depending on the particular orchestratorin use.

One or more optional telemetry node(s) 260 provide metrics, alarms,logging, and flow analysis. SDN architecture 200 telemetry leveragescloud native monitoring services, such as Prometheus, Elastic, Fluentd,Kinaba stack (EFK) and Influx TSDB. The SDN architecture componentmicroservices of configuration nodes 230, control nodes 232, computenodes, user interface 244, and analytics nodes (not shown) may producetelemetry data. This telemetry data may be consumed by services oftelemetry node(s) 260. Telemetry node(s) 260 may expose REST endpointsfor users and may support insights and event correlation.

Optional user interface 244 includes web user interface (UI) 306 and UIbackend 308 services. In general, user interface 244 providesconfiguration, monitoring, visualization, security, and troubleshootingfor the SDN architecture components.

Each of telemetry 260, user interface 244, configuration nodes 230,control nodes 232, and servers 12/compute nodes may be considered SDNarchitecture 200 nodes, in that each of these nodes is an entity toimplement functionality of the configuration, control, or data planes,or of the UI and telemetry nodes. Node scale is configured during “bringup,” and SDN architecture 200 supports automatic scaling of SDNarchitecture 200 nodes using orchestration system operators, such asKubernetes operators.

FIG. 4 is a block diagram illustrating example components of an SDNarchitecture, in accordance with techniques of this disclosure. In thisexample, SDN architecture 400 extends and uses Kubernetes API server fornetwork configuration objects that realize user intents for the networkconfiguration. Such configuration objects, in Kubernetes terminology,are referred to as custom resources and when persisted in SDNarchitecture are referred to simply as objects. Configuration objectsare mainly user intents (e.g., Virtual Networks, BGPaaS, Network Policy,Service Chaining, etc.).

SDN architecture 400 configuration nodes 230 may uses Kubernetes APIserver for configuration objects. In kubernetes terminology, these arecalled custom resources.

Kubernetes provides two ways to add custom resources to a cluster:

-   Custom Resource Definitions (CRDs) are simple and can be created    without any programming.-   API Aggregation requires programming but allows more control over    API behaviors, such as how data is stored and conversion between API    versions.

Aggregated APIs are subordinate API servers that sit behind the primaryAPI server, which acts as a proxy. This arrangement is called APIAggregation (AA). To users, it simply appears that the Kubernetes API isextended. CRDs allow users to create new types of resources withoutadding another API server. Regardless of how they are installed, the newresources are referred to as Custom Resources (CR) to distinguish themfrom native Kubernetes resources (e.g., Pods). CRDs were used in theinitial Config prototypes. The architecture may use the API ServerBuilder Alpha library to implement an aggregated API. API Server Builderis a collection of libraries and tools to build native Kubernetesaggregation extensions.

Usually, each resource in the Kubernetes API requires code that handlesREST requests and manages persistent storage of objects. The mainKubernetes API server 300 (implemented with API server microservices300A-300J) handles native resources and can also generically handlecustom resources through CRDs. Aggregated API 402 represents anaggregation layer that extends the Kubernetes API server 300 to allowfor specialized implementations for custom resources by writing anddeploying custom API server 301 (using custom API server microservices301A-301M). The main API server 300 delegates requests for the customresources to custom API server 301, thereby making such resourcesavailable to all of its clients.

In this way, API server 300 (e.g., kube-apiserver) receives theKubernetes configuration objects, native objects (pods, services) andcustom resources defined in accordance with techniques of thisdisclosure. Custom resources for SDN architecture 400 may includeconfiguration objects that, when an intended state of the configurationobject in SDN architecture 400 is realized, implements an intendednetwork configuration of SDN architecture 400. Custom resources maycorrespond to configuration schemas traditionally defined for networkconfiguration but that, according to techniques of this disclosure, areextended to be manipulable through aggregated API 402. Such customresources may be alternately termed and referred to herein as “customresources for SDN architecture configuration.” Each of the customresources for SDN architecture configuration may correspond to a type ofconfiguration object conventionally exposed by an SDN controller, but inaccordance with techniques described herein, the configuration objectsare exposed using custom resources and consolidated along withKubernetes native / built-in resources. These configuration objects mayinclude virtual network, bgp-as-a-service (BGPaaS), subnet, virtualrouter, service instance, project, physical interface, logicalinterface, node, network ipam, floating ip, alarm, alias ip, accesscontrol list, firewall policy, firewall rule, network policy, routetarget, routing instance, etc. Consequently, SDN architecture system 400supports a unified intent model, exposed by aggregated API 402, that isrealized by Kubernetes controllers 406A-406N and by custom resourcecontrollers 302 (shown in FIG. 4 as component microservices 302A-302L)that work to reconcile the actual state of the computing infrastructureincluding network elements with the intended state.

API server 300 aggregation layer sends API custom resources to theircorresponding, registered custom API server 300. There may be multiplecustom API servers / custom resource controllers to support differentkinds of custom resources. Custom API server 300 handles customresources for SDN architecture configuration and writes to configurationstore(s) 304, which may be etcd. Custom API server 300 may be host andexpose an SDN controller identifier allocation service that may berequired by custom resource controller 302.

Custom resource controller(s) 302 start to apply business logic to reachthe user’s intention provided with user intents configuration. Thebusiness logic is implemented as a reconciliation loop. FIG. 8 is ablock diagram illustrating an example of a custom controller for customresource(s) for SDN architecture configuration, according to techniquesof this disclosure. Customer controller 814 may represent an exampleinstance of custom resource controller 301. In the example illustratedin FIG. 8 , custom controller 814 can be associated with custom resource818. Custom resource 818 can be any custom resource for SDN architectureconfiguration. Custom controller 814 can include reconciler 816 thatincludes logic to execute a reconciliation loop in which customcontroller 814 observes 834 (e.g., monitors) a current state 832 ofcustom resource 818. In response to determining that a desired state 836does not match a current state 832, reconciler 816 can perform actionsto adjust 838 the state of the custom resource such that the currentstate 832 matches the desired state 836. A request may be received byAPI server 300 and relayed to custom API server 301 to change thecurrent state 832 of custom resource 818 to desired state 836.

In the case that API request 301 is a create request for a customresource, reconciler 816 can act on the create event for the instancedata for the custom resource. Reconciler 816 may create instance datafor custom resources that the requested custom resource depends on. Asan example, an edge node custom resource may depend on a virtual networkcustom resource, a virtual interface custom resource, and an IP addresscustom resource. In this example, when reconciler 816 receives a createevent on an edge node custom resource, reconciler 816 can also createthe custom resources that the edge node custom resource depends upon,e.g., a virtual network custom resource, a virtual interface customresource, and an IP address custom resource.

By default, custom resource controllers 302 are running anactive-passive mode and consistency is achieved using master election.When a controller pod starts it tries to create a ConfigMap resource inKubemetes using a specified key. If creation succeeds, that pod becomesmaster and starts processing reconciliation requests; otherwise itblocks trying to create ConfigMap in an endless loop.

Custom resource controller 300 may track the status of custom resourcesit creates. For example, a Virtual Network (VN) creates a RoutingInstance (RI) which creates a Route Target (RT). If the creation of aroute target fails, the routing instance status is degraded, and becauseof this the virtual network status is also degraded. Custom resourcecontroller 300 may therefore output a custom message indicating thestatus(es) of these custom resources, for troubleshooting. An exampleflow of creation, watch, and reconciliation among custom resource typesthat have dependencies on different custom resource types is illustratedin FIG. 9 .

The configuration plane as implemented by configuration nodes 230 havehigh availability. Configuration nodes 230 may be based on Kubernetes,including the kube-apiserver service (e.g., API server 300) and thestorage backend etcd (e.g., configuration store(s) 304). Effectively,aggregated API 402 implemented by configuration nodes 230 operates asthe front end for the control plane implemented by control nodes 232.The main implementation of API server 300 is kube-apiserver, which isdesigned to scale horizontally by deploying more instances. As shown,several instances of API server 300 can be run to load balance APIrequests and processing.

Configuration store(s) 304 may be implemented as etcd. Etcd is aconsistent and highly-available key value store used as the Kubemetesbacking store for cluster data.

In the example of FIG. 4 , servers 12 of SDN architecture 400 eachinclude an orchestration agent 420 and a containerized (or“cloud-native”) routing protocol daemon 324. These components of SDNarchitecture 400 are described in further detail below.

SDN controller manager 303 may operate as an interface betweenKubernetes core resources (Service, Namespace, Pod, Network Policy,Network Attachment Definition) and the extended SDN architectureresources (VirtualNetwork, RoutingInstance etc.). SDN controller manager303 watches the Kubernetes API for changes on both Kubernetes core andthe custom resources for SDN architecture configuration and, as aresult, can perform CRUD operations on the relevant resources.

In some examples, SDN controller manager 303 is a collection of one ormore Kubernetes custom controllers. In some examples, in single ormulti-cluster deployments, SDN controller manager 303 may run on theKubernetes cluster(s) it manages

SDN controller manager 303 listens to the following Kubernetes objectsfor Create, Delete, and Update events:

-   Pod-   Service-   NodePort-   Ingress-   Endpoint-   Namespace-   Deployment-   Network Policy

When these events are generated, SDN controller manager 303 createsappropriate SDN architecture objects, which are in turn defined ascustom resources for SDN architecture configuration. In response todetecting an event on an instance of a custom resource, whetherinstantiated by SDN controller manager 303 and/or through custom APIserver 301, control node 232 obtains configuration data for the instancefor the custom resource and configures a corresponding instance of aconfiguration object in SDN architecture 400.

For example, SDN controller manager 303 watches for the Pod creationevent and, in response, may create the following SDN architectureobjects: VirtualMachine (a workload/pod), VirtualMachineInterface (avirtual network interface), and an InstanceIP (IP address). Controlnodes 232 may then instantiate the SDN architecture objects, in thiscase, in a selected compute node.

As an example, based on a watch, control node 232A may detect an eventon an instance of first custom resource exposed by customer API server301A, where the first custom resource is for configuring some aspect ofSDN architecture system 400 and corresponds to a type of configurationobject of SDN architecture system 400. For instance, the type ofconfiguration object may be a firewall rule corresponding to the firstcustom resource. In response to the event, control node 232A may obtainconfiguration data for the firewall rule instance (e.g., the firewallrule specification) and provision the firewall rule in a virtual routerfor server 12A. Configuration nodes 230 and control nodes 232 mayperform similar operations for other custom resource with correspondingtypes of configuration objects for the SDN architecture, such as virtualnetwork, bgp-as-a-service (BGPaaS), subnet, virtual router, serviceinstance, project, physical interface, logical interface, node, networkipam, floating ip, alarm, alias ip, access control list, firewallpolicy, firewall rule, network policy, route target, routing instance,etc.

FIG. 5 is a block diagram of an example computing device, according totechniques described in this disclosure. Computing device 500 of FIG. 2may represent a real or virtual server and may represent an exampleinstance of any of servers 12 and may be referred to as a compute node,master/minion node, or host. Computing device 500 includes in thisexample, a bus 542 coupling hardware components of a computing device500 hardware environment. Bus 542 couples network interface card (NIC)530, storage disk 546, and one or more microprocessors 210 (hereinafter,“microprocessor 510”). NIC 530 may be SR-IOV-capable. A front-side busmay in some cases couple microprocessor 510 and memory device 524. Insome examples, bus 542 may couple memory device 524, microprocessor 510,and NIC 530. Bus 542 may represent a Peripheral Component Interface(PCI) express (PCIe) bus. In some examples, a direct memory access (DMA)controller may control DMA transfers among components coupled to bus542. In some examples, components coupled to bus 542 control DMAtransfers among components coupled to bus 542.

Microprocessor 510 may include one or more processors each including anindependent execution unit to perform instructions that conform to aninstruction set architecture, the instructions stored to storage media.Execution units may be implemented as separate integrated circuits (ICs)or may be combined within one or more multi-core processors (or“many-core” processors) that are each implemented using a single IC(i.e., a chip multiprocessor).

Disk 546 represents computer readable storage media that includesvolatile and/or non-volatile, removable and/or non-removable mediaimplemented in any method or technology for storage of information suchas processor-readable instructions, data structures, program modules, orother data. Computer readable storage media includes, but is not limitedto, random access memory (RAM), read-only memory (ROM), EEPROM, Flashmemory, CD-ROM, digital versatile discs (DVD) or other optical storage,magnetic cassettes, magnetic tape, magnetic disk storage or othermagnetic storage devices, or any other medium that can be used to storethe desired information and that can be accessed by microprocessor 510.

Main memory 524 includes one or more computer-readable storage media,which may include random-access memory (RAM) such as various forms ofdynamic RAM (DRAM), e.g., DDR2/DDR3 SDRAM, or static RAM (SRAM), flashmemory, or any other form of fixed or removable storage medium that canbe used to carry or store desired program code and program data in theform of instructions or data structures and that can be accessed by acomputer. Main memory 524 provides a physical address space composed ofaddressable memory locations.

Network interface card (NIC) 530 includes one or more interfaces 532configured to exchange packets using links of an underlying physicalnetwork. Interfaces 532 may include a port interface card having one ormore network ports. NIC 530 may also include an on-card memory to, e.g.,store packet data. Direct memory access transfers between the NIC 530and other devices coupled to bus 542 may read/write from/to the NICmemory.

Memory 524, NIC 530, storage disk 546, and microprocessor 510 mayprovide an operating environment for a software stack that includes anoperating system kernel 580 executing in kernel space. Kernel 580 mayrepresent, for example, a Linux, Berkeley Software Distribution (BSD),another Unix-variant kernel, or a Windows server operating systemkernel, available from Microsoft Corp. In some instances, the operatingsystem may execute a hypervisor and one or more virtual machines managedby the hypervisor. Example hypervisors include Kernel-based VirtualMachine (KVM) for the Linux kernel, Xen, ESXi available from VMware,Windows Hyper-V available from Microsoft, and other open-source andproprietary hypervisors. The term hypervisor can encompass a virtualmachine manager (VMM). An operating system that includes kernel 580provides an execution environment for one or more processes in userspace 545.

Kernel 580 includes a physical driver 525 to use the network interfacecard 530. Network interface card 530 may also implement SR-IOV to enablesharing the physical network function (I/O) among one or more virtualexecution elements, such as containers 529A or one or more virtualmachines (not shown in FIG. 5 ). Shared virtual devices such as virtualfunctions may provide dedicated resources such that each of the virtualexecution elements may access dedicated resources of NIC 530, whichtherefore appears to each of the virtual execution elements as adedicated NIC. Virtual functions may represent lightweight PCIefunctions that share physical resources with a physical function used byphysical driver 525 and with other virtual functions. For anSR-IOV-capable NIC 530, NIC 530 may have thousands of available virtualfunctions according to the SR-IOV standard, but for I/O-intensiveapplications the number of configured virtual functions is typicallymuch smaller.

Computing device 500 may be coupled to a physical network switch fabricthat includes an overlay network that extends switch fabric fromphysical switches to software or “virtual” routers of physical serverscoupled to the switch fabric, including virtual router 506. Virtualrouters may be processes or threads, or a component thereof, executed bythe physical servers, e.g., servers 12 of FIG. 1 , that dynamicallycreate and manage one or more virtual networks usable for communicationbetween virtual network endpoints. In one example, virtual routersimplement each virtual network using an overlay network, which providesthe capability to decouple an endpoint’s virtual address from a physicaladdress (e.g., IP address) of the server on which the endpoint isexecuting. Each virtual network may use its own addressing and securityscheme and may be viewed as orthogonal from the physical network and itsaddressing scheme. Various techniques may be used to transport packetswithin and across virtual networks over the physical network. The term“virtual router” as used herein may encompass an Open vSwitch (OVS), anOVS bridge, a Linux bridge, Docker bridge, or other device and/orsoftware that is located on a host device and performs switching,bridging, or routing packets among virtual network endpoints of one ormore virtual networks, where the virtual network endpoints are hosted byone or more of servers 12. In the example computing device 500 of FIG. 5, virtual router 506 executes within user space as a DPDK-based virtualrouter, but virtual router 506 may execute within a hypervisor, a hostoperating system, a host application, or a virtual machine in variousimplementations.

Virtual router 506 may replace and subsume the virtual routing/bridgingfunctionality of the Linux bridge/OVS module that is commonly used forKubernetes deployments of pods 502. Virtual router 506 may performbridging (e.g., E-VPN) and routing (e.g., L3VPN, IP-VPNs) for virtualnetworks. Virtual router 506 may perform networking services such asapplying security policies, NAT, multicast, mirroring, and loadbalancing.

Virtual router 506 can be executing as a kernel module or as a userspace DPDK process (virtual router 506 is shown here in user space 545).Virtual router agent 514 may also be executing in user space. In theexample computing device 500, virtual router 506 executes within userspace as a DPDK-based virtual router, but virtual router 506 may executewithin a hypervisor, a host operating system, a host application, or avirtual machine in various implementations. Virtual router agent 514 hasa connection to network controller 24 using a channel, which is used todownload configurations and forwarding information. Virtual router agent514 programs this forwarding state to the virtual router data (or“forwarding”) plane represented by virtual router 506. Virtual router506 and virtual router agent 514 may be processes. Virtual router 506and virtual router agent 514 containerized/cloud-native.

Virtual router 506 may replace and subsume the virtual routing/bridgingfunctionality of the Linux bridge/OVS module that is commonly used forKubernetes deployments of pods 502. Virtual router 506 may performbridging (e.g., E-VPN) and routing (e.g., L3VPN, IP-VPNs) for virtualnetworks. Virtual router 506 may perform networking services such asapplying security policies, NAT, multicast, mirroring, and loadbalancing.

Virtual router 506 may be multi-threaded and execute on one or moreprocessor cores. Virtual router 506 may include multiple queues. Virtualrouter 506 may implement a packet processing pipeline. The pipeline canbe stitched by the virtual router agent 514 from the simplest to themost complicated manner depending on the operations to be applied to apacket. Virtual router 506 may maintain multiple instances of forwardingbases. Virtual router 506 may access and update tables using RCU (ReadCopy Update) locks.

To send packets to other compute nodes or switches, virtual router 506uses one or more physical interfaces 532. In general, virtual router 506exchanges overlay packets with workloads, such as VMs or pods 502.Virtual router 506 has multiple virtual network interfaces (e.g., vifs).These interfaces may include the kernel interface, vhost0, forexchanging packets with the host operating system; an interface withvirtual router agent 514, pkt0, to obtain forwarding state from thenetwork controller and to send up exception packets. There may be one ormore virtual network interfaces corresponding to the one or morephysical network interfaces 532. Other virtual network interfaces ofvirtual router 506 are for exchanging packets with the workloads.

In a kernel-based deployment of virtual router 506 (not shown), virtualrouter 506 is installed as a kernel module inside the operating system.Virtual router 506 registers itself with the TCP/IP stack to receivepackets from any of the desired operating system interfaces that itwants to. The interfaces can be bond, physical, tap (for VMs), veth (forcontainers) etc. Virtual router 506 in this mode relies on the operatingsystem to send and receive packets from different interfaces. Forexample, the operating system may expose a tap interface backed by avhost-net driver to communicate with VMs. Once virtual router 506registers for packets from this tap interface, the TCP/IP stack sendsall the packets to it. Virtual router 506 sends packets via an operatingsystem interface. In addition, NIC queues (physical or virtual) arehandled by the operating system. Packet processing may operate ininterrupt mode, which generates interrupts and may lead to frequentcontext switching. When there is a high packet rate, the overheadattendant with frequent interrupts and context switching may overwhelmthe operating system and lead to poor performance.

In a DPDK-based deployment of virtual router 506 (shown in FIG. 5 ),virtual router 506 is installed as a user space 545 application that islinked to the DPDK library. This may lead to faster performance than akernel-based deployment, particularly in the presence of high packetrates. The physical interfaces 532 are used by the poll mode drivers(PMDs) of DPDK rather the kernel’s interrupt-based drivers. Theregisters of physical interfaces 532 may be exposed into user space 545in order to be accessible to the PMDs; a physical interface 532 bound inthis way is no longer managed by or visible to the host operatingsystem, and the DPDK-based virtual router 506 manages the physicalinterface 532. This includes packet polling, packet processing, andpacket forwarding. In other words, user packet processing steps areperformed by the virtual router 506 DPDK data plane. The nature of this“polling mode” makes the virtual router 506 DPDK data plane packetprocessing/forwarding much more efficient as compared to the interruptmode when the packet rate is high. There are comparatively fewinterrupts and context switching during packet I/O, compared tokernel-mode virtual router 506, and interrupt and context switchingduring packet I/O may in some cases be avoided altogether.

In general, each of pods 502A-502B may be assigned one or more virtualnetwork addresses for use within respective virtual networks, where eachof the virtual networks may be associated with a different virtualsubnet provided by virtual router 506. Pod 502B may be assigned its ownvirtual layer three (L3) IP address, for example, for sending andreceiving communications but may be unaware of an IP address of thecomputing device 500 on which the pod 502B executes. The virtual networkaddress may thus differ from the logical address for the underlying,physical computer system, e.g., computing device 500.

Computing device 500 includes a virtual router agent 514 that controlsthe overlay of virtual networks for computing device 500 and thatcoordinates the routing of data packets within computing device 500. Ingeneral, virtual router agent 514 communicates with network controller24 for the virtualization infrastructure, which generates commands tocreate virtual networks and configure network virtualization endpoints,such as computing device 500 and, more specifically, virtual router 506,as a well as virtual network interface 212. By configuring virtualrouter 506 based on information received from network controller 24,virtual router agent 514 may support configuring network isolation,policy-based security, a gateway, source network address translation(SNAT), a load-balancer, and service chaining capability fororchestration.

In one example, network packets, e.g., layer three (L3) IP packets orlayer two (L2) Ethernet packets generated or consumed by the containers529A-529B within the virtual network domain may be encapsulated inanother packet (e.g., another IP or Ethernet packet) that is transportedby the physical network. The packet transported in a virtual network maybe referred to herein as an “inner packet” while the physical networkpacket may be referred to herein as an “outer packet” or a “tunnelpacket.” Encapsulation and/or de-capsulation of virtual network packetswithin physical network packets may be performed by virtual router 506.This functionality is referred to herein as tunneling and may be used tocreate one or more overlay networks. Besides IPinIP, other exampletunneling protocols that may be used include IP over Generic RouteEncapsulation (GRE), VxLAN, Multiprotocol Label Switching (MPLS) overGRE, MPLS over User Datagram Protocol (UDP), etc. Virtual router 506performs tunnel encapsulation/decapsulation for packets sourcedby/destined to any containers of pods 502, and virtual router 506exchanges packets with pods 502 via bus 542 and/or a bridge of NIC 530.

As noted above, a network controller 24 may provide a logicallycentralized controller for facilitating operation of one or more virtualnetworks. The network controller 24 may, for example, maintain a routinginformation base, e.g., one or more routing tables that store routinginformation for the physical network as well as one or more overlaynetworks. Virtual router 506 implements one or more virtual routing andforwarding instances (VRFs), such as VRF 222A, for respective virtualnetworks for which virtual router 506 operates as respective tunnelendpoints. In general, each of the VRFs stores forwarding informationfor the corresponding virtual network and identifies where data packetsare to be forwarded and whether the packets are to be encapsulated in atunneling protocol, such as with a tunnel header that may include one ormore headers for different layers of the virtual network protocol stack.Each of the VRFs may include a network forwarding table storing routingand forwarding information for the virtual network.

NIC 530 may receive tunnel packets. Virtual router 506 processes thetunnel packet to determine, from the tunnel encapsulation header, thevirtual network of the source and destination endpoints for the innerpacket. Virtual router 506 may strip the layer 2 header and the tunnelencapsulation header to internally forward only the inner packet. Thetunnel encapsulation header may include a virtual network identifier,such as a VxLAN tag or MPLS label, that indicates a virtual network,e.g., a virtual network corresponding to VRF 222A. VRF 222A may includeforwarding information for the inner packet. For instance, VRF 222A maymap a destination layer 3 address for the inner packet to virtualnetwork interface 212. VRF 222A forwards the inner packet via virtualnetwork interface 212 to pod 502A in response.

Containers 529A may also source inner packets as source virtual networkendpoints. Container 529A, for instance, may generate a layer 3 innerpacket destined for a destination virtual network endpoint that isexecuted by another computing device (i.e., not computing device 500) orfor another one of containers. Container 529A may sends the layer 3inner packet to virtual router 506 via the virtual network interfaceattached to VRF 222A.

Virtual router 506 receives the inner packet and layer 2 header anddetermines a virtual network for the inner packet. Virtual router 506may determine the virtual network using any of the above-describedvirtual network interface implementation techniques (e.g., macvlan,veth, etc.). Virtual router 506 uses the VRF 222A corresponding to thevirtual network for the inner packet to generate an outer header for theinner packet, the outer header including an outer IP header for theoverlay tunnel and a tunnel encapsulation header identifying the virtualnetwork. Virtual router 506 encapsulates the inner packet with the outerheader. Virtual router 506 may encapsulate the tunnel packet with a newlayer 2 header having a destination layer 2 address associated with adevice external to the computing device 500, e.g., a TOR switch 16 orone of servers 12. If external to computing device 500, virtual router506 outputs the tunnel packet with the new layer 2 header to NIC 530using physical function 221. NIC 530 outputs the packet on an outboundinterface. If the destination is another virtual network endpointexecuting on computing device 500, virtual router 506 routes the packetto the appropriate one of virtual network interfaces 212, 213.

In some examples, a controller for computing device 500 (e.g., networkcontroller 24 of FIG. 1 ) configures a default route in each of pods 502to cause the virtual machines 224 to use virtual router 506 as aninitial next hop for outbound packets. In some examples, NIC 530 isconfigured with one or more forwarding rules to cause all packetsreceived from virtual machines 224 to be switched to virtual router 506.

Pod 502A includes one or more application containers 529A. Pod 502Bincludes an instance of containerized routing protocol daemon (cRPD)560. Container platform 588 includes container runtime 590,orchestration agent 592, service proxy 593, and CNI 570.

Container engine 590 includes code executable by microprocessor 510.Container runtime 590 may be one or more computer processes. Containerengine 590 runs containerized applications in the form of containers529A-529B. Container engine 590 may represent a Dockert, rkt, or othercontainer engine for managing containers. In general, container engine590 receives requests and manages objects such as images, containers,networks, and volumes. An image is a template with instructions forcreating a container. A container is an executable instance of an image.Based on directives from controller agent 592, container engine 590 mayobtain images and instantiate them as executable containers in pods502A-502B.

Service proxy 593 includes code executable by microprocessor 510.Service proxy 593 may be one or more computer processes. Service proxy593 monitors for the addition and removal of service and endpointsobjects, and it maintains the network configuration of the computingdevice 500 to ensure communication among pods and containers, e.g.,using services. Service proxy 593 may also manage iptables to capturetraffic to a service’s virtual IP address and port and redirect thetraffic to the proxy port that proxies a backed pod. Service proxy 593may represent a kube-proxy for a minion node of a Kubemetes cluster. Insome examples, container platform 588 does not include a service proxy593 or the service proxy 593 is disabled in favor of configuration ofvirtual router 506 and pods 502 by CNI 570.

Orchestration agent 592 includes code executable by microprocessor 510.Orchestration agent 592 may be one or more computer processes.Orchestration agent 592 may represent a kubelet for a minion node of aKubemetes cluster. Orchestration agent 592 is an agent of anorchestrator, e.g., orchestrator 23 of FIG. 1 , that receives containerspecification data for containers and ensures the containers execute bycomputing device 500. Container specification data may be in the form ofa manifest file sent to orchestration agent 592 from orchestrator 23 orindirectly received via a command line interface, HTTP endpoint, or HTTPserver. Container specification data may be a pod specification (e.g., aPodSpec—a YAML (Yet Another Markup Language) or JSON object thatdescribes a pod) for one of pods 502 of containers. Based on thecontainer specification data, orchestration agent 592 directs containerengine 590 to obtain and instantiate the container images for containers529, for execution of containers 529 by computing device 500.

Orchestration agent 592 instantiates or otherwise invokes CNI 570 toconfigure one or more virtual network interfaces for each of pods 502.For example, orchestration agent 592 receives a container specificationdata for pod 502A and directs container engine 590 to create the pod502A with containers 529A based on the container specification data forpod 502A. Orchestration agent 592 also invokes the CNI 570 to configure,for pod 502A, virtual network interface for a virtual networkcorresponding to VRFs 222A. In this example, pod 502A is a virtualnetwork endpoint for a virtual network corresponding to VRF 222A.

CNI 570 may obtain interface configuration data for configuring virtualnetwork interfaces for pods 502. Virtual router agent 514 operates as avirtual network control plane module for enabling network controller 24to configure virtual router 506. Unlike the orchestration control plane(including the container platforms 588 for minion nodes and the masternode(s), e.g., orchestrator 23), which manages the provisioning,scheduling, and managing virtual execution elements, a virtual networkcontrol plane (including network controller 24 and virtual router agent514 for minion nodes) manages the configuration of virtual networksimplemented in the data plane in part by virtual routers 506 of theminion nodes. Virtual router agent 514 communicates, to CNI 570,interface configuration data for virtual network interfaces to enable anorchestration control plane element (i.e., CNI 570) to configure thevirtual network interfaces according to the configuration statedetermined by the network controller 24, thus bridging the gap betweenthe orchestration control plane and virtual network control plane. Inaddition, this may enable a CNI 570 to obtain interface configurationdata for multiple virtual network interfaces for a pod and configure themultiple virtual network interfaces, which may reduce communication andresource overhead inherent with invoking a separate CNI 570 forconfiguring each virtual network interface.

Containerized routing protocol daemons are described in U.S. ApplicationNo. 17/649,632, filed Feb. 1, 2022, which is incorporated by referenceherein in its entirety.

FIG. 6 is a block diagram of an example computing device operating as acompute node for one or more clusters for an SDN architecture system, inaccordance with techniques of this disclosure. Computing device 1300 mayrepresent one or more real or virtual servers. Computing device 1300 mayin some instances implement one or more master nodes for respectiveclusters, or for multiple clusters.

Scheduler 1322, API server 300A, controller 406A, custom API server301A, custom resource controller 302A, controller manager 1326, SDNcontroller manager 1325, control node 232A, and configuration store1328, although illustrated and described as being executed by a singlecomputing device 1300, may be distributed among multiple computingdevices that make up a computing system or hardware/server cluster. Eachof the multiple computing devices, in other words, may provide ahardware operating environment for one or more instances of any one ormore of scheduler 1322, API server 300A, controller 406A, custom APIserver 301A, custom resource controller 302A, network controller manager1326, network controller 1324, SDN controller manager 1325, control node232A, or configuration store 1328.

Computing device 1300 includes in this example, a bus 1342 couplinghardware components of a computing device 1300 hardware environment. Bus1342 couples network interface card (NIC) 1330, storage disk 1346, andone or more microprocessors 1310 (hereinafter, “microprocessor 1310”). Afront-side bus may in some cases couple microprocessor 1310 and memorydevice 1344. In some examples, bus 1342 may couple memory device 1344,microprocessor 1310, and NIC 1330. Bus 1342 may represent a PeripheralComponent Interface (PCI) express (PCIe) bus. In some examples, a directmemory access (DMA) controller may control DMA transfers amongcomponents coupled to bus 242. In some examples, components coupled tobus 1342 control DMA transfers among components coupled to bus 1342.

Microprocessor 1310 may include one or more processors each including anindependent execution unit to perform instructions that conform to aninstruction set architecture, the instructions stored to storage media.Execution units may be implemented as separate integrated circuits (ICs)or may be combined within one or more multi-core processors (or“many-core” processors) that are each implemented using a single IC(i.e., a chip multiprocessor).

Disk 1346 represents computer readable storage media that includesvolatile and/or non-volatile, removable and/or non-removable mediaimplemented in any method or technology for storage of information suchas processor-readable instructions, data structures, program modules, orother data. Computer readable storage media includes, but is not limitedto, random access memory (RAM), read-only memory (ROM), EEPROM, Flashmemory, CD-ROM, digital versatile discs (DVD) or other optical storage,magnetic cassettes, magnetic tape, magnetic disk storage or othermagnetic storage devices, or any other medium that can be used to storethe desired information and that can be accessed by microprocessor 1310.

Main memory 1344 includes one or more computer-readable storage media,which may include random-access memory (RAM) such as various forms ofdynamic RAM (DRAM), e.g., DDR2/DDR3 SDRAM, or static RAM (SRAM), flashmemory, or any other form of fixed or removable storage medium that canbe used to carry or store desired program code and program data in theform of instructions or data structures and that can be accessed by acomputer. Main memory 1344 provides a physical address space composed ofaddressable memory locations.

Network interface card (NIC) 1330 includes one or more interfaces 3132configured to exchange packets using links of an underlying physicalnetwork. Interfaces 3132 may include a port interface card having one ormore network ports. NIC 1330 may also include an on-card memory to,e.g., store packet data. Direct memory access transfers between the NIC1330 and other devices coupled to bus 1342 may read/write from/to theNIC memory.

Memory 1344, NIC 1330, storage disk 1346, and microprocessor 1310 mayprovide an operating environment for a software stack that includes anoperating system kernel 1314 executing in kernel space. Kernel 1314 mayrepresent, for example, a Linux, Berkeley Software Distribution (BSD),another Unix-variant kernel, or a Windows server operating systemkernel, available from Microsoft Corp. In some instances, the operatingsystem may execute a hypervisor and one or more virtual machines managedby hypervisor. Example hypervisors include Kernel-based Virtual Machine(KVM) for the Linux kernel, Xen, ESXi available from VMware, WindowsHyper-V available from Microsoft, and other open-source and proprietaryhypervisors. The term hypervisor can encompass a virtual machine manager(VMM). An operating system that includes kernel 1314 provides anexecution environment for one or more processes in user space 1345.Kernel 1314 includes a physical driver 1327 to use the network interfacecard 230.

Computing device 1300 may be coupled to a physical network switch fabricthat includes an overlay network that extends switch fabric fromphysical switches to software or virtual routers of physical serverscoupled to the switch fabric, such virtual routers 21. Computing device1300 may use one or more dedicated virtual networks to configure minionnodes of a cluster.

API server 300A, scheduler 1322, controller 406A, custom API server301A, custom resource controller 302A, controller manager 1326, andconfiguration store 1328 may implement a master node for a cluster andbe alternatively referred to as “master components.” The cluster may bea Kubemetes cluster and the master node a Kubemetes master node, inwhich case the master components are Kubernetes master components.

Each of API server 300A, controller 406A, custom API server 301A, andcustom resource controller 302A includes code executable bymicroprocessor 1310. Custom API server 301A validates and configuresdata for custom resources for SDN architecture configuration. A servicemay be an abstraction that defines a logical set of pods and the policyused to access the pods. The set of pods implementing a service areselected based on the service definition. A service may be implementedin part as, or otherwise include, a load balancer. API server 300A andcustom API server 301A may implement a Representational State Transfer(REST) interface to process REST operations and provide the frontend, aspart of the configuration plane for an SDN architecture, to acorresponding cluster’s shared state stored to configuration store 1328.API server 300A may represent a Kubemetes API server.

Configuration store 1328 is a backing store for all cluster data.Cluster data may include cluster state and configuration data.Configuration data may also provide a backend for service discoveryand/or provide a locking service. Configuration store 1328 may beimplemented as a key value store. Configuration store 1328 may be acentral database or distributed database. Configuration store 1328 mayrepresent an etcd store. Configuration store 1328 may represent aKubemetes configuration store.

Scheduler 1322 includes code executable by microprocessor 1310.Scheduler 1322 may be one or more computer processes. Scheduler 1322monitors for newly created or requested virtual execution elements(e.g., pods of containers) and selects a minion node on which thevirtual execution elements are to run. Scheduler 1322 may select aminion node based on resource requirements, hardware constraints,software constraints, policy constraints, locality, etc. Scheduler 1322may represent a Kubemetes scheduler.

In general, API server 1320 may invoke the scheduler 1322 to schedule apod. Scheduler 1322 may select a minion node and returns an identifierfor the selected minion node to API server 1320, which may write theidentifier to the configuration store 1328 in association with the pod.API server 1320 may invoke the orchestration agent 310 for the selectedminion node, which may cause the container engine 208 for the selectedminion node to obtain the pod from a storage server and create thevirtual execution element on the minion node. The orchestration agent310 for the selected minion node may update the status for the pod tothe API server 1320, which persists this new state to the configurationstore 1328. In this way, computing device 1300 instantiates new pods inthe computing infrastructure 8.

Controller manager 1326 includes code executable by microprocessor 1310.Controller manager 1326 may be one or more computer processes.Controller manager 1326 may embed the core control loops, monitoring ashared state of a cluster by obtaining notifications from API Server1320. Controller manager 1326 may attempt to move the state of thecluster toward the desired state. Example controller 406A and customresource controller 302A may be managed by the controller manager 1326.Other controllers may include a replication controller, endpointscontroller, namespace controller, and service accounts controller.Controller manager 1326 may perform lifecycle functions such asnamespace creation and lifecycle, event garbage collection, terminatedpod garbage collection, cascading-deletion garbage collection, nodegarbage collection, etc. Controller manager 1326 may represent aKubernetes Controller Manager for a Kubernetes cluster.

A network controller for an SDN architecture described herein mayprovide cloud networking for a computing architecture operating over anetwork infrastructure. Cloud networking may include private clouds forenterprise or service providers, infrastructure as a service (IaaS), andvirtual private clouds (VPCs) for cloud service providers (CSPs). Theprivate cloud, VPC, and IaaS use cases may involve a multi-tenantvirtualized data centers, such as that described with respect to FIG. 1. In such cases, multiple tenants in a data center share the samephysical resources (physical servers, physical storage, physicalnetwork). Each tenant is assigned its own logical resources (virtualmachines, containers, or other form of virtual execution elements;virtual storage; virtual networks). These logical resources are isolatedfrom each other, unless specifically allowed by security policies. Thevirtual networks in the data center may also be interconnected to aphysical IP VPN or L2 VPN.

The network controller (or “SDN controller”) may provide networkfunction virtualization (NFV) to networks, such as business edgenetworks, broadband subscriber management edge networks, and mobile edgenetworks. NFV involves orchestration and management of networkingfunctions such as a Firewalls, Intrusion Detection or PreventionsSystems (IDS / IPS), Deep Packet Inspection (DPI), caching, Wide AreaNetwork (WAN) optimization, etc. in virtual machines, containers, orother virtual execution elements instead of on physical hardwareappliances.

SDN controller manager 1325 includes code executable by microprocessor1310. SDN controller manager 1325 may be one or more computer processes.SDN controller manager 1325 operates as an interface between theorchestration-oriented elements (e.g., scheduler 1322, API server 300Aand custom API server 301A, controller manager 1326, and configurationstore 1328). In general, SDN controller manager 1325 monitors thecluster for new Kubernetes native objects (e.g., pods and services). SDNcontroller manager 1325 may isolate pods in virtual networks and connectpods with services.

SDN controller manager 1325 may be executed as a container of the masternode for a cluster. In some cases, using SDN controller manager 1325enables disabling the service proxies of minion nodes (e.g., theKubernetes kube-proxy) such that all pod connectivity is implementedusing virtual routers, as described herein.

Components of the network controller 24 may operate as a CNI forKubernetes and may support multiple deployment modes. CNI 17, CNI 750are the compute node interfaces for this overall CNI framework formanaging networking for Kubernetes. The deployment modes can be dividedinto two categories: (1) an SDN architecture cluster as a CNI integratedinto a workload Kubernetes cluster, and (2) an SDN architecture clusteras a CNI that is separate from the workload Kubernetes clusters.

Integrated with Workload Kubernetes Cluster

Components of the network controller 24 (e.g., custom API server 301,custom resource controller 302, SDN controller manager 1325, and controlnodes 232) are running in the managed Kubernetes cluster on masternodes, close to the Kubernetes controller components. In this mode,components of network controller 24 are effectively part of the sameKubernetes cluster as the workloads.

Separate From Workload Kubernetes Clusters

Components of the network controller 24 will be executed by a separateKubernetes cluster from the workload Kubernetes clusters.

SDN controller manager 1325 may use a controller framework for theorchestration platform to listen for (or otherwise monitor for) changesin objects that are defined in the Kubernetes native API and to addannotations to some of these objects. The annotations may be labels orother identifiers specifying properties of the objects (e.g., “VirtualNetwork Green”). SDN controller manager 1325 is a component of the SDNarchitecture that listens to Kubernetes core resources (such as Pod,NetworkPolicy, Service, etc.) events and converts those to customresources for SDN architecture configuration as needed. The CNI plugin(e.g., CNIs 17, 570) is an SDN architecture component supporting theKubernetes networking plugin standard: container network interface.

SDN controller manager 1325 may create a network solution for theapplication using the REST interface exposed by aggregated API 402 todefine network objects such as virtual networks, virtual networkinterfaces, and access control policies. Network controller 24components may implement the network solution in the computinginfrastructure by, e.g., configuring the one or more virtual network andvirtual network interfaces in the virtual routers. (This is merely oneexample of an SDN configuration.)

The following example deployment configuration for this applicationconsists of a pod and the virtual network information for the pod:

        apiVersion: v1         kind: Pod         metadata:         name: multi-net-pod          annotations:          networks: '[            { “name”: “red-network” },           { “name”: “blue-network” },          ]'{ “name”: “default/extns-network” }         spec:         containers:          - image: busybox           command:           - sleep            - “3600”          imagePullPolicy: IfNotPresent           name: busybox          stdin: true           tty: true         restartPolicy: Always

This metadata information may be copied to each pod replica created bythe controller manager 1326. When the SDN controller manager 1325 isnotified of these pods, SDN controller manager 1325 may create virtualnetworks as listed in the annotations (“red-network”, “blue-network”,and “default/extns-network” in the above example) and create, for eachof the virtual networks, a virtual network interface per-pod replica(e.g., pod 202A) with a unique private virtual network address from acluster-wide address block (e.g. 10.0/16) for the virtual network.

Additional techniques in accordance with this disclosure are describedbelow. Contrail is an example network controller architecture. ContrailCNI may be a CNI developed for Contrail. A cloud-native Contrailcontroller may be an example of a network controller described in thisdisclosure, such as network controller 24.

FIG. 7A is a block diagram illustrating control / routing planes forunderlay network and overlay network configuration using an SDNarchitecture, according to techniques of this disclosure. FIG. 7B is ablock diagram illustrating a configured virtual network to connect podsusing a tunnel configured in the underlay network, according totechniques of this disclosure.

Network controller 24 for the SDN architecture may use distributed orcentralized routing plane architectures. The SDN architecture may use acontainerized routing protocol daemon (process).

From the perspective of network signaling, the routing plane can workaccording to a distributed model, where a cRPD runs on every computenode in the cluster. This essentially means that the intelligence isbuilt into the compute nodes and involves complex configurations at eachnode. The route reflector (RR) in this model may not make intelligentrouting decisions but is used as a relay to reflect routes between thenodes. A distributed container routing protocol daemon (cRPD) is arouting protocol process that may be used wherein each compute node runsits own instance of the routing daemon. At the same time, a centralizedcRPD master instance may act as an RR to relay routing informationbetween the compute nodes. The routing and configuration intelligence isdistributed across the nodes with an RR at the central location.

The routing plane can alternatively work according to a more centralizedmodel, in which components of network controller runs centrally andabsorbs the intelligence needed to process configuration information,construct the network topology, and program the forwarding plane intothe virtual routers. The virtual router agent is a local agent toprocess information being programmed by the network controller. Thisdesign leads to facilitates more limited intelligence required at thecompute nodes and tends to lead to simpler configuration states.

The centralized control plane provides for the following:

-   Allows for the agent routing framework to be simpler and lighter.    The complexity and limitations of BGP are hidden from the agent.    There is no need for the agent to understand concepts like    route-distinguishers, route-targets, etc. The agents just exchange    prefixes and build its forwarding information accordingly-   Control nodes can do more than routing. They build on the virtual    network concept and can generate new routes using route replication    and re-origination (for instance to support features like service    chaining and inter-VN routing, among other use cases).-   Building the BUM tree for optimal broadcast and multicast    forwarding.

Note that the control plane has a distributed nature for certainaspects. As a control plane supporting distributed functionality, itallows each local virtual router agent to publish its local routes andsubscribe for configuration on a need-to-know basis.

It makes sense then to think of the control plane design from a toolingPOV and use tools at hand appropriately where they fit best. Considerthe set of pros and cons of contrail-bgp and cRPD.

The following functionalities may be provided by cRPDs or control nodesof network controller 24.

0199 Routing Daemon / Process

Both control nodes and cRPDs can act as routing daemons implementingdifferent protocols and having the capability to program routinginformation in the forwarding plane.

cRPD implements routing protocols with a rich routing stack thatincludes interior gateway protocols (IGPs) (e.g., intermediate system tointermediate system (IS-IS)), BGP-LU, BGP-CT, SR-MPLS/SRv6,bidirectional forwarding detection (BFD), path computation elementprotocol (PCEP), etc. It can also be deployed to provide control planeonly services such as a route-reflector and is popular in internetrouting use-cases due to these capabilities.

Control nodes 232 also implement routing protocols but are predominantlyBGP-based. Control nodes 232 understands overlay networking. Controlnodes 232 provide a rich feature set in overlay virtualization and caterto SDN use cases. Overlay features such as virtualization (using theabstraction of a virtual network) and service chaining are very popularamong telco and cloud providers. cRPD may not in some cases includesupport for such overlay functionality. However, the rich feature set ofCRPD provides strong support for the underlay network.

0203 Network Orchestration/Automation

Routing functionality is just one part of the control nodes 232. Anintegral part of overlay networking is orchestration. Apart fromproviding overlay routing, control nodes 232 help in modeling theorchestration functionality and provide network automation. Central toorchestration capabilities of control nodes 232 is an ability to use thevirtual network (and related objects)-based abstraction to model networkvirtualization. Control nodes 232 interface with the configuration nodes230 to relay configuration information to both the control plane and thedata plane. Control nodes 232 also assist in building overlay trees formulticast layer 2 and layer 3. For example, a control node may build avirtual topology of the cluster it serves to achieve this. cRPD does nottypically include such orchestration capabilities.

0205 High Availability and Horizontal Scalability

Control node design is more centralized while cRPD is more distributed.There is a cRPD worker node running on each compute node. Control nodes232 on the other hand do not run on the compute and can even run on aremote cluster (i.e., separate and in some cases geographically remotefrom the workload cluster). Control nodes 232 also provide horizontalscalability for HA and run in active-active mode. The compute load isshared among the control nodes 232. cRPD on the other hand does nottypically provide horizontal scalability. Both control nodes 232 andcRPD may provide HA with graceful restart and may allow for data planeoperation in headless mode-wherein the virtual router can run even ifthe control plane restarts.

The control plane should be more than just a routing daemon. It shouldsupport overlay routing and network orchestration/automation, while cRPDdoes well as a routing protocol in managing underlay routing. cRPD,however, typically lacks network orchestration capabilities and does notprovide strong support for overlay routing.

Accordingly, in some examples, the SDN architecture may have cRPD on thecompute nodes as shown in FIGS. 7A-7B. FIG. 7A illustrates SDNarchitecture 700, which may represent an example implementation SDNarchitecture 200 or 400. In SDN architecture 700, cRPD 324 runs on thecompute nodes and provide underlay routing to the forwarding plane whilerunning a centralized (and horizontally scalable) set of control nodes232 providing orchestration and overlay services. In some examples,instead of running cRPD 324 on the compute nodes, a default gateway maybe used.

cRPD 324 on the compute nodes provides rich underlay routing to theforwarding plane by interacting with virtual router agent 514 usinginterface 540, which may be a gRPC interface. The virtual router agentinterface may permit programming routes, configuring virtual networkinterfaces for the overlay, and otherwise configuring virutal router506. This is described in further detail in U.S. Application No.17/649,632. At the same time, one or more control nodes 232 run asseparate pods providing overlay services. SDN architecture 700 may thusobtain both a rich overlay and orchestration provided by control nodes232 and modern underlay routing by cRPD 324 on the compute nodes tocomplement control nodes 232. A separate cRPD controller 720 may be usedto configure the cRPDs 324. cRPD controller 720 may be a device /element management system, network management system, orchestrator, auser interface / CLI, or other controller. cRPDs 324 run routingprotocols and exchange routing protocol messages with routers, includingother cRPDs 324. Each of cRPDs 324 may be a containerized routingprotocol process and effectively operates as a software-only version ofa router control plane.

The enhanced underlay routing provided by cRPD 324 may replace thedefault gateway at the forwarding plane and provide a rich routing stackfor use cases that can be supported. In some examples that do not usecRPD 324, virtual router 506 will rely on the default gateway forunderlay routing. In some examples, cRPD 324 as the underlay routingprocess will be restricted to program only the default inet(6).0 fabricwith control plane routing information. In such examples, non-defaultoverlay VRFs may be programmed by control nodes 232.

FIGS. 7A-7B illustrate the dual routing/control plane solution describedabove. In FIG. 7A, cRPD 324 provides underlay routing / forwardinginformation to virtual router agent 514, similar in some respect to howa router control plane programs a router forwarding / data plane.

As shown in FIG. 7B, cRPDs 324 exchange routing information usable tocreate tunnels through the underlay network 702 for VRFs. Tunnel 710 isan example and connects virtual routers 506 of server 12A and server12X. Tunnel 710 may represent an segment routing (SR) or SRv6 tunnel, aGeneric Route Encapsulation (GRE) tunnel, and IP-in-IP tunnel, an LSP,or other tunnel. Control nodes 232 leverages tunnel 710 to createvirtual network 712 connecting pods 22 of server 12A and server 12X thatare attached to the VRF for the virtual network.

As noted above, cRPD 324 and virtual router agent 514 may exchangerouting information using a gRPC interface, and virtual router agent5145 may program virtual router 506 with configuration using the gRPCinterface. As also noted, control nodes 232 may be used for overlay andorchestration while cRPD 324 may be used for managing the underlayrouting protocols. Virtual router agent 514 may use gRPC interface withcRPD 324 while using XMPP to communicate with the control node and adomain name service (DNS).

The gRPC model works well for cRPD 324 since there may be a workerrunning on every compute node, and the virtual router agent 314 acts asthe gRPC server exposing services for the client (cRPD 324) to use toprogram routing and configuration information (for underlay). gRPC isthus an attractive as a solution when compared to XMPP. In particular,it transports data as a binary stream and there is no added overhead inencoding/decoding data to be sent over it.

In some examples, control nodes 232 may interface with virtual routeragents 514 using XMPP. With virtual router agent 514 acting as the gRPCserver, cRPD 324 acts as the gRPC client. This would mean that theclient (cRPD) needs to initiate the connection towards the server(vRouter Agent). SDN architecture 700, virtual router agent 514 choosesthe set of control nodes 232 it will subscribe to (since there aremultiple control nodes). In that aspect, the control node 232 acts asthe server and the virtual router agent 514 connects as the client andsubscribes for updates.

With gRPC, the control node 232 would need to pick the virtual routeragents 514 it needs to connect to and then subscribe as a client. Sincethe control node 232 does not run on every compute node, this wouldrequire implementing an algorithm to choose the virtual router agents514 it can subscribe to. Further, the control nodes 232 need tosynchronize this information amongst each other. This also complicatesthe case when restarts happen and there is a need for synchronizationbetween the control nodes 232 to pick the agents they serve. Featuressuch as Graceful Restart (GR) and Fast Convergence have already beenimplemented on top of XMPP, XMPP is already lightweight and effective.Therefore, XMPP may be advantageous over gRPC for control node 232 tovirtual router agent 514 communications.

Additional enhancements to control nodes 232 and the use thereof are asfollows. HA and horizontal scalability with three control-nodes. Likeany routing platform, it should be sufficient to have just two controlnodes 232 to satisfy the HA requirements. In many cases, this isadvantageous. (However, one or more control nodes 232 may be used.) Forexample, it provides more deterministic infrastructure and in-line withstandard routing best-practices. Each virtual router agent 514 isattached to a unique pair of control nodes 232 to avoid randomness. Withtwo control nodes 232, debugging may be simpler. In addition, edgereplication for constructing multicast / broadcast trees may besimplified with only two control notes 232. Currently, since vRouteragents 314 only connect to two of the three control nodes, all thecontrol nodes may not have the complete picture of the tree for sometime and rely on BGP to sync states between them. This is exacerbatedwith three control nodes 232 since virtual router agents 314 may choosetwo at random. If there were only two control nodes 232, every virtualrouter agent 314 would connect to the same control nodes. This, in turn,would mean that control nodes 232 need not rely on BGP to sync statesand will have the same picture of the multicast tree.

SDN architecture 200 may provide for ingress replication as analternative to edge-replication and provide users the option. Ingressreplication can be viewed as a special degenerate case of generaloverlay multicast trees. In practice, however, the signaling of ingressreplication trees is much simpler than the signaling of general overlaymulticast trees. With ingress replication, every virtual router 21 endsup with a tree with itself as the root and every other vrouter as theleaf. A virtual router 21 going down should theoretically not result inrebuilding the tree. Note that the performance of ingress replicationdeteriorates with larger clusters. However, it works well for smallerclusters. Furthermore, multicast is not a popular and prevalentrequirement for many customers. It is mostly limited to transportbroadcast BUM traffic, which only happens initially.

0219 Configuration Handling Module Enhancements

In convention SDN architectures, the network controller handles theorchestration for all use cases. The configuration nodes translateintents into configuration objects based on the data model and writethem into a database (e.g., Cassandra). In some cases, at the same time,a notification is sent to all clients awaiting the configuration, e.g.,via RabbitMQ.

Control nodes not only acts as BGP speakers but also have aconfiguration handling module that reads configuration objects from thedatabase in the following ways. First, when a control node comes up (orrestarts), it connects to and reads all configuration directly from thedatabase. Second, a control node may be also a messaging client. Whenthere are updates to configuration objects, control nodes receive amessaging notification that lists the objects that have been updated.This again causes the configuration handling module to read objects fromthe database.

The configuration handling module reads configuration objects for boththe control plane (BGP related configuration) and the vRouter forwardingplane. The configuration may be stored as a graph with objects as nodesand relationships as links. This graph can then be downloaded to theclients (BGP/cRPD and/or vRouter agent).

In accordance with techniques of this disclosure, the conventionalconfiguration API server and messaging service are in some examplesreplaced by Kube api-server (API server 300 and custom API server 301)and the previous Cassandra database by etcd in Kubemetes. With thischange, clients interested in configuration objects can directly do awatch on the etcd database to get updates rather than rely on RabbitMQnotifications.

0224 Controller Orchestration for CRPD

BGP configuration can be provided to cRPDs 324. In some examples, cRPDcontroller 720 may be a Kubernetes controller catered to the to developits own controller catered to the Kubernetes space and implements CRDsrequired for orchestration and provisioning cRPDs 324.

0226 Distributed Configuration Handling

As mentioned earlier in this section, the configuration handling modulemay be part of control nodes 232. It reads configuration directly from adatabase, converts the data into JSON format and stores it in its localIFMAP database as a graph with objects as nodes and the relationshipbetween them as links. This graph then gets downloaded to interestedvirtual router agents 514 on the compute nodes via XMPP. Virtual routeragent 514 constructs the IFMAP based dependency graph locally as well tostore these objects.

IFMAP as an intermediate module and the need for storing a dependencygraph can be avoided by having the virtual router agents 514 directly doa watch on the etcd server in API server 300. The same model can be usedby cRPD 324 running on the compute nodes. This will avoid the need forthe IFMAP-XMPP config channel. A Kubernetes configuration client (forcontrol node 232) can be used as part of this config. This client canalso be used by the virtual router agents.

This can, however, increase the number of clients reading configurationfrom the etcd server, especially in clusters with hundreds of computenodes. Adding more watchers eventually causes the write rate to drop andthe event rate to fall short of the ideal, etcd’s gRPC proxyrebroadcasts from one server watcher to many client watchers. The gRPCproxy coalesces multiple client watchers (c-watchers) on the same key orrange into a single watcher (s-watcher) connected to an etcd server. Theproxy broadcasts all events from the s-watcher to its c-watchers.Assuming N clients watch the same key, one gRPC proxy can reduce thewatch load on the etcd server from N to 1. Users can deploy multiplegRPC proxies to further distribute server load. These clients share oneserver watcher; the proxy effectively offloads resource pressure fromthe core cluster. By adding proxies, etcd can serve one million eventsper second.

0230 DNS/Named in the SDN Architecture

In previous architectures, DNS services are provided by contrail-dns andcontrail-named processes working in conjunction to provide DNS servicesto VMs in the network. Named acts as the DNS server that provides animplementation of the BIND protocol, contrail-dns receives updates fromthe vrouter-agent and pushes these records to named.

Four DNS modes are supported in the system, IPAM configuration canselect the DNS mode required.

1. None - No DNS support for the VMs.

2. Default DNS server - DNS resolution for the VMs is done based on thename server configuration in the server infrastructure. When a VM gets aDHCP response, the subnet default gateway is configured as the DNSserver for the VM. DNS requests that the VM sends to this defaultgateway are resolved via the (fabric) name servers configured on therespective compute nodes and the responses are sent back to the VM.

3. Tenant DNS server - Tenants can use their own DNS servers using thismode. A list of servers can be configured in the IPAM, which are thensent in the DHCP response to the VM as DNS server(s). DNS requests thatthe VM sends are routed as any other data packet based on the availablerouting information.

4. Virtual DNS server - In this mode, the system supports virtual DNSservers, providing DNS servers that resolve the DNS requests from theVMs. We can define multiple virtual domain name servers under eachdomain in the system. Each virtual domain name server is anauthoritative server for the DNS domain configured.

The SDN architecture described herein is efficient in the DNS servicesit provides. Customers in the cloud native world to be benefited by thevaried DNS services. However, with the move to next generationKubernetes-based architecture, the SDN architecture may instead usecoreDNS for any DNS services.

Data Plane

The Data plane consists of two components: virtual router agent 514 (akaAgent) and virtual router forwarding plane 506 (also referred to as DPDKvRouter / Kernel vRouter) Agent 514 in the SDN architecture solution isresponsible to manage the data plane component. Agent 514 establishesXMPP neighborships with two control nodes 232, then exchanges therouting information with them. The vRouter agent 514 also dynamicallygenerates flow entries and injects them into the virtual router 506.This gives instructions to virtual router 506 about how to forwardpackets.

Responsibilities of Agent 514 may include: Interface with control node232 to obtain the configuration. Translate received configuration into aform that datapath can understand (e.g., translate the data model fromIFMap to the data model used by datapath), Interface with control node232 to manage routes. And collect and export statistics from datapath toa monitoring solution.

Virtual router 506 implements the data-plane functionality that mayallow a virtual network interface to be associated with a VRF. Each VRFhas its own forwarding and flow tables, while the MPLS and VXLAN tablesare global within virtual router 506. The forwarding tables may containroutes for both the IP and MAC addresses of destinations and theIP-to-MAC association is used to provide proxy ARP capability. Thevalues of labels in the MPLS table are selected by virtual router 506when VM/Container interfaces come up and are only locally significant tothat vRouter. The VXLAN Network Identifiers are global across all theVRFs of the same virtual network in different virtual router 506 withina domain.

In some examples, each virtual network has a default gateway addressallocated to it, and each VM or container interface receives thataddress in the DHCP response received when initializing. When a workloadsends a packet to an address outside its subnet, it will ARP for the MACcorresponding to the IP address of the gateway, and virtual router 506responds with its own MAC address. Thus, virtual router 506 may supporta fully distributed default gateway function for all the virtualnetworks.

The following are examples of packet flow forwarding as implemented byvirtual routers 506.

Packet Flows Between VMs/Container Interface in the Same Subnet

The worker node could be VM or Container Interface. In some examples,the packet processing proceeds as follows:

-   VM1/Container Interface needs to send a packet to VM2, so virtual    router 506 first looks up its own DNS cache for the IP address, but    since this is the first packet, there is no entry.-   VM1 sends a DNS request to the DNS server address that was supplied    in the DHCP response when its interface came up.-   The virtual router 506 traps the DNS request and forwards it to the    DNS server running in the SDN architecture controller.-   The DNS server in the controller responds with the IP address of VM2-   The virtual router 506 sends the DNS response to VM1-   VM1 needs to form an Ethernet frame, so needs the MAC address for    VM2. It checks its own ARP cache, but there is no entry, since this    is the first packet.-   VM1 sends out an ARP request.-   The virtual router 506 traps the ARP request and looks up the MAC    address for IP-VM2 in its own forwarding tables and finds the    association in the L2/L3 routes that the controller sent it for VM2.-   The virtual router 506 sends an ARP reply to VM 1 with the MAC    address of VM2-   A TCP timeout occurs in the network stack of VM1-   The network stack of VM1 1 retries sending the packet, and this time    finds the MAC address of VM2 in the ARP cache and can form an    Ethernet frame and send it out.-   The virtual router 506 looks up the MAC address for VM2 and finds an    encapsulation route. The virtual router 506 builds the outer header    and sends the resulting packet to server S2.-   The virtual router 506 on server S2 decapsulates the packet and    looks up the MPLS label to identify the virtual interface to send    the original Ethernet frame into. The Ethernet frame is sent into    the interface and received by VM2.

Packet Flow Between VMs In Different Subnets

In some examples, the sequence when sending packets to destinations in adifferent subnet is similar except that the virtual router 506 respondsas the default gateway. VM1 will send the packet in an Ethernet framewith the MAC address of the default gateway whose IP address wassupplied in the DHCP response that the virtual router 506 supplied whenVM1 booted. When VM1 does an ARP request for the gateway IP address, thevirtual router 506 responds with its own MAC address. When VM1 sends anEthernet frame using that gateway MAC address, the virtual router 506uses the destination IP address of the packet inside the frame to lookup the forwarding table in the VRF to find a route, which will be via anencapsulation tunnel to the host that the destination is running on.

FIG. 10 is a flowchart illustrating an example mode of operations 1000for a network controller of a software-defined networking architecturesystem, according to techniques of this disclosure. The networkcontroller includes an API server 300 for processing requests foroperations on native resources of a container orchestration system(1001). The network also controller includes a custom API server 301 forprocessing requests for operations on custom resources for SDNarchitecture configuration (1002). Each of the custom resources for SDNarchitecture configuration corresponds to a type of configuration objectin the SDN architecture system. The network controller also includes acontrol node that, in response to detecting an event on an instance of afirst custom resource of the custom resources, obtains configurationdata for the instance of the first custom resource and configures acorresponding instance of a configuration object in the SDN architecture(1004).

The techniques described herein may be implemented in hardware,software, firmware, or any combination thereof. Various featuresdescribed as modules, units or components may be implemented together inan integrated logic device or separately as discrete but interoperablelogic devices or other hardware devices. In some cases, various featuresof electronic circuitry may be implemented as one or more integratedcircuit devices, such as an integrated circuit chip or chipset.

If implemented in hardware, this disclosure may be directed to anapparatus such as a processor or an integrated circuit device, such asan integrated circuit chip or chipset. Alternatively or additionally, ifimplemented in software or firmware, the techniques may be realized atleast in part by a computer-readable data storage medium comprisinginstructions that, when executed, cause a processor to perform one ormore of the methods described above. For example, the computer-readabledata storage medium may store such instructions for execution by aprocessor.

A computer-readable medium may form part of a computer program product,which may include packaging materials. A computer-readable medium maycomprise a computer data storage medium such as random access memory(RAM), read-only memory (ROM), non-volatile random access memory(NVRAM), electrically erasable programmable read-only memory (EEPROM),Flash memory, magnetic or optical data storage media, and the like. Insome examples, an article of manufacture may comprise one or morecomputer-readable storage media.

In some examples, the computer-readable storage media may comprisenon-transitory media. The term “non-transitory” may indicate that thestorage medium is not embodied in a carrier wave or a propagated signal.In certain examples, a non-transitory storage medium may store data thatcan, over time, change (e.g., in RAM or cache).

The code or instructions may be software and/or firmware executed byprocessing circuitry including one or more processors, such as one ormore digital signal processors (DSPs), general purpose microprocessors,application-specific integrated circuits (ASICs), field-programmablegate arrays (FPGAs), or other equivalent integrated or discrete logiccircuitry. Accordingly, the term “processor,” as used herein may referto any of the foregoing structure or any other structure suitable forimplementation of the techniques described herein. In addition, in someaspects, functionality described in this disclosure may be providedwithin software modules or hardware modules.

1. A network controller for a software-defined networking (SDN)architecture system, the network controller comprising: processingcircuitry; a configuration node configured for execution by theprocessing circuitry; and a control node configured for execution by theprocessing circuitry, wherein the configuration node includes anapplication programming interface (API) server to process requests foroperations on native resources of a container orchestration system andincludes a custom API server to process requests for operations oncustom resources for SDN architecture configuration, wherein each of thecustom resources for SDN architecture configuration corresponds to atype of configuration object in the SDN architecture system, and whereinthe control node is configured to, in response to detecting an event onan instance of a first custom resource of the custom resources, obtainconfiguration data for the instance of the first custom resource andconfigure a corresponding instance of a configuration object in the SDNarchitecture.
 2. The network controller of claim 1, wherein theconfiguration node, for each type of configuration object in the SDNarchitecture system, includes a different custom resource controller andimplements a different one of the custom resources for SDN architectureconfiguration.
 3. The network controller of claim 2, wherein the customAPI server is configured to receive a first request for an operation onthe instance of the first custom resource and apply the operation tocreate intended state data for the instance of the first custom resourcein a configuration store, and wherein the custom resource controller forthe first custom resource is configured to, in response to the creationof the intended state data, reconcile actual state of the instance ofthe first custom resource to the intended state data in theconfiguration store.
 4. The network controller of claim 3, wherein theevent on the instance of the first custom resource of the customresources comprises the creation of the intended state data.
 5. Thenetwork controller of claim 1, wherein the instance of the first customresource is stored to a configuration store, and wherein the controlnode is configured to detect the event on the instance of the firstcustom resource using a watch on the configuration store.
 6. The networkcontroller of claim 1, wherein the API server is configured to receive afirst request for an operation on an instance of a native resource ofthe container orchestration system and apply the operation to createintended state data for the instance of the native resource in aconfiguration store.
 7. The network controller of claim 6, wherein theconfiguration node includes a controller configured, in response to thecreation of the intended state data, reconcile actual state of theinstance of the first custom resource to the intended state data in theconfiguration store to reconcile the instance of the native resource tothe intended state data in the configuration store.
 8. The networkcontroller of claim 1, wherein the API server is configured to: receivea first request for an operation on the instance of the first customresource; and in response to determining the request relates to thefirst custom resource, delegate the first request to the custom APIserver.
 9. The network controller of claim 1, wherein the configurationnode comprises an SDN controller manager configured to: in response todetecting a first request to create an instance of a native resource ofthe container orchestration system, create the instance of the firstcustom resource.
 10. The network controller of claim 9, wherein theevent on the instance of the first custom resource comprises thecreation of the instance of the first custom resource.
 11. The networkcontroller of claim 1, wherein the SDN controller manager comprises acustom controller that is registered with the API server to receiveevents for the native resource.
 12. The network controller of claim 1,wherein the first custom resource is virtual network, and wherein toconfigure the corresponding instance of the configuration object in theSDN architecture, the control node configures an instance of a virtualnetwork in a compute node of the SDN architecture.
 13. The networkcontroller of claim 1, wherein the network controller is implemented bya Kubernetes cluster comprising a compute node of the SDN architecture.14. A method comprising: processing, by an application programminginterface (API) server implemented by a configuration node of a networkcontroller for a software-defined networking (SDN) architecture system,requests for operations on native resources of a container orchestrationsystem; processing, by a custom API server implemented by theconfiguration node, requests for operations on custom resources for SDNarchitecture configuration, wherein each of the custom resources for SDNarchitecture configuration corresponds to a type of configuration objectin the SDN architecture system; detecting, by a control node of thenetwork controller, an event on an instance of a first custom resourceof the custom resources; and by the control node, in response todetecting the event on the instance of the first custom resource,obtaining configuration data for the instance of the first customresource and configuring a corresponding instance of a configurationobject in the SDN architecture.
 15. The method of claim 14, wherein theconfiguration node, for each type of configuration object in the SDNarchitecture system, includes a different custom resource controller andimplements a different one of the custom resources for SDN architectureconfiguration.
 16. The method of claim 14, further comprising:receiving, by the API server, a first request for an operation on theinstance of the first custom resource; and in response to determiningthe request relates to the first custom resource, by the API server,delegating the first request to the custom API server.
 17. The method ofclaim 14, further comprising: by an SDN controller manager implementedby the configuration node, in response to detecting a first request tocreate an instance of a native resource of the container orchestrationsystem, creating the instance of the first custom resource.
 18. Themethod of claim 14, wherein the event on the instance of the firstcustom resource comprises the creation of the instance of the firstcustom resource.
 19. The method of claim 14, wherein the first customresource is virtual network, and wherein configuring the correspondinginstance of the configuration object in the SDN architecture comprisesconfiguring an instance of a virtual network in a compute node of theSDN architecture.
 20. A non-transitory computer-readable mediumcomprising instructions for causing processing circuitry to: process, byan application programming interface (API) server implemented by aconfiguration node of a network controller for a software-definednetworking (SDN) architecture system, requests for operations on nativeresources of a container orchestration system; process, by a custom APIserver implemented by the configuration node, requests for operations oncustom resources for SDN architecture configuration, wherein each of thecustom resources for SDN architecture configuration corresponds to atype of configuration object in the SDN architecture system; detect, bya control node of the network controller, an event on an instance of afirst custom resource of the custom resources; and by the control node,in response to detecting the event on the instance of the first customresource, obtain configuration data for the instance of the first customresource and configure a corresponding instance of a configurationobject in the SDN architecture.